Spiral CT of the chest: comparison of cine and film-based viewing

More scanning, but not zooming, is associated with diagnostic accuracy in evaluating digital breast pathology slides

Diagnoses of medical images can invite strikingly diverse strategies for image navigation and visual search. In computed tomography screening for lung nodules, distinct strategies, termed scanning and drilling, relate to both radiologists' clinical experience and accuracy in lesion detection. Here, we examined associations between search patterns and accuracy for pathologists (N = 92) interpreting a diverse set of breast biopsy images. While changes in depth in volumetric images reveal new structures through movement in the z-plane, in digital pathology changes in depth are associated with increased magnification. Thus, "drilling" in radiology may be more appropriately termed "zooming" in pathology. We monitored eye-movements and navigation through digital pathology slides to derive metrics of how quickly the pathologists moved through XY (scanning) and Z (zooming) space. Prior research on eye-movements in depth has categorized clinicians as either "scanners" or "drillers." In contrast, we found that there was no reliable association between a clinician's tendency to scan or zoom while examining digital pathology slides. Thus, in the current work we treated scanning and zooming as continuous predictors rather than categorizing as either a "scanner" or "zoomer." In contrast to prior work in volumetric chest images, we found significant associations between accuracy and scanning rate but not zooming rate. These findings suggest fundamental differences in the relative value of information types and review behaviors across two image formats. Our data suggest that pathologists gather critical information by scanning on a given plane of depth, whereas radiologists drill through depth to interrogate critical features.

Characteristics of expert search behavior in volumetric medical image interpretation

Purpose: Experienced radiologists have enhanced global processing ability relative to novices, allowing experts to rapidly detect medical abnormalities without performing an exhaustive search. However, evidence for global processing models is primarily limited to two-dimensional image interpretation, and it is unclear whether these findings generalize to volumetric images, which are widely used in clinical practice. We examined whether radiologists searching volumetric images use methods consistent with global processing models of expertise. In addition, we investigated whether search strategy (scanning/drilling) differs with experience level. Approach: Fifty radiologists with a wide range of experience evaluated chest computed-tomography scans for lung nodules while their eye movements and scrolling behaviors were tracked. Multiple linear regressions were used to determine: (1) how search behaviors differed with years of experience and the number of chest CTs evaluated per week and (2) which search behaviors predicted better performance. Results: Contrary to global processing models based on 2D images, experience was unrelated to measures of global processing (saccadic amplitude, coverage, time to first fixation, search time, and depth passes) in this task. Drilling behavior was associated with better accuracy than scanning behavior when controlling for observer experience. Greater image coverage was a strong predictor of task accuracy. Conclusions: Global processing ability may play a relatively small role in volumetric image interpretation, where global scene statistics are not available to radiologists in a single glance. Rather, in volumetric images, it may be more important to engage in search strategies that support a more thorough search of the image.

What do we know about volumetric medical image interpretation?: a review of the basic science and medical image perception literatures

Interpretation of volumetric medical images represents a rapidly growing proportion of the workload in radiology. However, relatively little is known about the strategies that best guide search behavior when looking for abnormalities in volumetric images. Although there is extensive literature on two-dimensional medical image perception, it is an open question whether the conclusions drawn from these images can be generalized to volumetric images. Importantly, volumetric images have distinct characteristics (e.g., scrolling through depth, smooth-pursuit eye-movements, motion onset cues, etc.) that should be considered in future research. In this manuscript, we will review the literature on medical image perception and discuss relevant findings from basic science that can be used to generate predictions about expertise in volumetric image interpretation. By better understanding search through volumetric images, we may be able to identify common sources of error, characterize the optimal strategies for searching through depth, or develop new training and assessment techniques for radiology residents.

Eye Movements in Medical Image Perception: A Selective Review of Past, Present and Future

The eye movements of experts, reading medical images, have been studied for many years. Unlike topics such as face perception, medical image perception research needs to cope with substantial, qualitative changes in the stimuli under study due to dramatic advances in medical imaging technology. For example, little is known about how radiologists search through 3D volumes of image data because they simply did not exist when earlier eye tracking studies were performed. Moreover, improvements in the affordability and portability of modern eye trackers make other, new studies practical. Here, we review some uses of eye movements in the study of medical image perception with an emphasis on newer work. We ask how basic research on scene perception relates to studies of medical 'scenes' and we discuss how tracking experts' eyes may provide useful insights for medical education and screening efficiency.

Evaluation of human observer performance on lesion detectability in single-slice and multislice dedicated breast cone beam CT images with breast anatomical background

PURPOSE

We evaluate the lesion detectability using human and model observer studies in single-slice and multislice cone beam computed tomography (CBCT) images with a breast anatomical background. The purposes of this work are (a) to compare human observer detectability between single-slice and multislice images for different signal sizes and noise structures, (b) to investigate the effect of different multislice viewing modes (i.e., sequential and simultaneous) on the detectability by a human observer, and (c) to predict the detectability by a human observer in single-slice and multislice images using single-slice channelized Hotelling observer (ssCHO) and multislice CHO (msCHO), respectively.

METHODS

Breast anatomical background is modeled using a power law spectrum of mammograms and the lesion is modeled with a spherical signal. We conduct signal-known-exactly and background-known-statistically detection tasks on transverse and longitudinal images reconstructed using the Feldkamp-Davis-Kress algorithm with Hanning and Ram-Lak weighted ramp filters. The human observer study is conducted on three different viewing modes: single-slice, and sequential and simultaneous multislice. To predict the detectability by a human observer, we use ssCHO and msCHO with anthropomorphic channels (i.e., dense difference-of-Gaussian (D-DOG) and Gabor channels) and internal noise.

RESULTS

The detectability by a human observer increases for multislice images compared to single-slice images. For multislice images, the sequential viewing mode yields higher detectability than the simultaneous viewing mode. However, the relative rank of detectability by a human observer for different signal sizes, image planes, and reconstruction filters is not much different between the viewing modes. Detectability by CHO with internal noise shows good correlation with that of the human observer for all viewing modes.

CONCLUSIONS

Detectability by a human observer in CBCT images with breast anatomical background is affected by the image viewing mode, and the effect of the viewing mode depends on the signal size and noise structure. D-DOG and Gabor CHO with internal noise predict the detectability by a human observer well for both the single-slice and multislice image viewing modes.

Variations in the functional visual field for detection of lung nodules on chest computed tomography: Impact of nodule size, distance, and local lung complexity

PURPOSE

To explore the characteristics that impact lung nodule detection by peripheral vision when searching for lung nodules on chest CT-scans.

METHODS

This study was approved by the local IRB and is HIPAA compliant. A simulated primary (1°) target mass (2 × 2 × 5 cm) was embedded into 5 cm thick subvolumes (SV) extracted from three unenhanced lung MDCT scans (64 row, 1.25 mm thickness, 0.7 mm increment). One of 30 solid, secondary nodules with either 3-4 mm and 5-8 mm diameters were embedded into 192 of 207 SVs. The secondary nodule was placed at a random depth within each SV, a transverse distance of 2.5, 5, 7.5, or 10 mm, and along one of eight rays cast every 45° from the center of the 1° mass. Video recordings of transverse paging in cranio-caudal direction were created for each SV (frame rate three sections/sec). Six radiologists observed each cine-loop once while gaze-tracking hardware assured that gaze was centered on the 1° mass. Each radiologist assigned a confidence rating (0-5) to the detection of a secondary nodule and indicated its location. Detection sensitivity was analyzed relative to secondary nodule size, transverse distance, radial orientation, and lung complexity. Lung complexity was characterized by the number of particles (connected pixels) and the sum of the area of all particles above a -500 HU threshold within regions of interest around the 1° mass and secondary nodule.

RESULTS

Using a proportional odds logistic regression model and eliminating redundant predictors, models fit individually to each reader resulted in the following decreasing order of association based on greatest reduction in Akaike Information Criterion: secondary nodule diameter (6/6 readers, P < 0.001), distance from central mass (6/6 readers, P < 0.001), lung complexity particle count (5/6 readers, P = 0.05), and lung complexity particle area (3/6 readers, P = 0.03). Substantial inter-reader differences in sensitivity to decreasing nodule diameter, distance, and complexity characteristics were observed.

CONCLUSIONS

Of the investigated parameters, secondary nodule size, distance from the gaze center and lung complexity (particle number and area) significantly impact nodule detection with peripheral vision.

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks

In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.

Let's Use Cognitive Science to Create Collaborative Workstations

When informed by an understanding of cognitive science, radiologists' workstations could become collaborative to improve radiologists' performance and job satisfaction. The authors review relevant literature and present several promising areas of research, including image toggling, eye tracking, cognitive computing, intelligently restricted messaging, work habit tracking, and innovative input devices. The authors call for more research in "perceptual design," a promising field that can complement advances in computer-aided detection.

Computational assessment of visual search strategies in volumetric medical images

When searching through volumetric images [e.g., computed tomography (CT)], radiologists appear to use two different search strategies: "drilling" (restrict eye movements to a small region of the image while quickly scrolling through slices), or "scanning" (search over large areas at a given depth before moving on to the next slice). To computationally identify the type of image information that is used in these two strategies, 23 naïve observers were instructed with either "drilling" or "scanning" when searching for target T's in 20 volumes of faux lung CTs. We computed saliency maps using both classical two-dimensional (2-D) saliency, and a three-dimensional (3-D) dynamic saliency that captures the characteristics of scrolling through slices. Comparing observers' gaze distributions with the saliency maps showed that search strategy alters the type of saliency that attracts fixations. Drillers' fixations aligned better with dynamic saliency and scanners with 2-D saliency. The computed saliency was greater for detected targets than for missed targets. Similar results were observed in data from 19 radiologists who searched five stacks of clinical chest CTs for lung nodules. Dynamic saliency may be superior to the 2-D saliency for detecting targets embedded in volumetric images, and thus "drilling" may be more efficient than "scanning."

Image toggling saves time in mammography

When two images are perfectly aligned, even subtle differences are readily detected when the images are "toggled" back and forth in the same location. However, substantial changes between two photographs can be missed if the images are misaligned ("change blindness"). Nevertheless, recent work from our lab, testing nonradiologists, suggests that toggling misaligned photographs leads to superior performance compared to side-by-side viewing (SBS). In order to determine if a benefit of toggling misaligned images may be observed in clinical mammography, we developed an image toggling technique where pairs of new and prior breast imaging exam images could be efficiently toggled back and forth. Twenty-three radiologists read 10 mammograms evenly divided in toggle and SBS modes. The toggle mode led to a 6-s benefit in reaching a decision [[Formula: see text], [Formula: see text]]. The toggle viewing mode also led to a 5% improvement in diagnostic accuracy, though in our small sample this effect was not statistically reliable. Time savings were found even though successive mammograms were not perfectly aligned. Given the ever-increasing caseload for radiologists, this simple manipulation of how the images are viewed could save valuable time in clinical practice, allowing radiologists to read more cases or spend more time on difficult cases.

Adaptive Statistical Iterative Reconstruction-Applied Ultra-Low-Dose CT with Radiography-Comparable Radiation Dose: Usefulness for Lung Nodule Detection

Objective

To assess the performance of adaptive statistical iterative reconstruction (ASIR)-applied ultra-low-dose CT (ULDCT) in detecting small lung nodules.

Materials and Methods

Thirty patients underwent both ULDCT and standard dose CT (SCT). After determining the reference standard nodules, five observers, blinded to the reference standard reading results, independently evaluated SCT and both subsets of ASIR- and filtered back projection (FBP)-driven ULDCT images. Data assessed by observers were compared statistically.

Results

Converted effective doses in SCT and ULDCT were 2.81 ± 0.92 and 0.17 ± 0.02 mSv, respectively. A total of 114 lung nodules were detected on SCT as a standard reference. There was no statistically significant difference in sensitivity between ASIR-driven ULDCT and SCT for three out of the five observers (p = 0.678, 0.735, < 0.01, 0.038, and < 0.868 for observers 1, 2, 3, 4, and 5, respectively). The sensitivity of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT in three out of the five observers (p < 0.01 for three observers, and p = 0.064 and 0.146 for two observers). In jackknife alternative free-response receiver operating characteristic analysis, the mean values of figure-of-merit (FOM) for FBP, ASIR-driven ULDCT, and SCT were 0.682, 0.772, and 0.821, respectively, and there were no significant differences in FOM values between ASIR-driven ULDCT and SCT (p = 0.11), but the FOM value of FBP-driven ULDCT was significantly lower than that of ASIR-driven ULDCT and SCT (p = 0.01 and 0.00).

Conclusion

Adaptive statistical iterative reconstruction-driven ULDCT delivering a radiation dose of only 0.17 mSv offers acceptable sensitivity in nodule detection compared with SCT and has better performance than FBP-driven ULDCT.

Scanners and drillers: characterizing expert visual search through volumetric images

Modern imaging methods like computed tomography (CT) generate 3-D volumes of image data. How do radiologists search through such images? Are certain strategies more efficient? Although there is a large literature devoted to understanding search in 2-D, relatively little is known about search in volumetric space. In recent years, with the ever-increasing popularity of volumetric medical imaging, this question has taken on increased importance as we try to understand, and ultimately reduce, errors in diagnostic radiology. In the current study, we asked 24 radiologists to search chest CTs for lung nodules that could indicate lung cancer. To search, radiologists scrolled up and down through a "stack" of 2-D chest CT "slices." At each moment, we tracked eye movements in the 2-D image plane and coregistered eye position with the current slice. We used these data to create a 3-D representation of the eye movements through the image volume. Radiologists tended to follow one of two dominant search strategies: "drilling" and "scanning." Drillers restrict eye movements to a small region of the lung while quickly scrolling through depth. Scanners move more slowly through depth and search an entire level of the lung before moving on to the next level in depth. Driller performance was superior to the scanners on a variety of metrics, including lung nodule detection rate, percentage of the lung covered, and the percentage of search errors where a nodule was never fixated.

Non-solid lung nodules on low-dose computed tomography: comparison of detection rate between 3 visualization techniques

Objective: To compare various visualization techniques for the detection of non-solid nodules in low-dose lung cancer screening computed tomography (CT) scans. Methods: An enriched sample of 216 male lung cancer screening subjects aged 60.4 ± 6.0 years was used. Two blinded independent readers searched for non-solid nodules on 5-mm multiplanar reconstructions, 1-mm slices and 7-mm maximum intensity projections (trial protocol). The reference standard was a consensus diagnosis of all non-solid nodules reported at least once. Results: Twenty-three individuals (10.6%) had in total 34 non-solid nodules. Interobserver agreement was good (Cohen kappa 0.89–0.95). For both observers, we found no differences between the 3 viewing techniques (P > 0.13). Conclusion: In low-dose lung cancer screening CT scans, we were unable to find a viewing technique superior to that used in the trial by experienced observers who focused on non-solid nodule detection.

Subcentimeter pulmonary nodules detected in patients with sarcoma

Background. Subcentimeter pulmonary nodules are being detected with increasing frequency in patients with sarcoma due to the greater use of chest CT, the advent of helical (spiral) CT scanning and multidetector scanners, and the attendant decrease in image section thickness.Assessing the clinical significance of these pulmonary nodules is of particular importance in sarcoma patients, due to the frequent occurrence of pulmonary metastasis from sarcomas.

Purpose. This article reviews the technical advances that have contributed to the increased detection of subcentimeter pulmonary nodules, statistics about subcentimeter pulmonary nodules and options for evaluating such nodules.

Imaging requirements in the practice of pulmonary metastasectomy

The primary imaging modality for the detection of pulmonary metastases is computed tomography (CT). Ideally, a helical CT scan with 3- to 5-mm reconstruction thickness or a volumetric thin section scanning should be performed within 4 weeks of pulmonary metastasectomy. A period of observation to see whether further metastases develop does not seem to allow better patient selection. If positron emission tomography is available, it may identify the extrathoracic metastatic sites in 10 to 15% of patients. Despite helical CT scan, palpation identifies the metastases not detected by imaging in 20 to 25% of patients and remains the standard. No data define the optimal interval for follow-up surveillance imaging.

Observer accuracy in the detection of pulmonary nodules on CT: effect of cine frame rate

AIM

To assess the effect of cine frame rate on the accuracy of the detection of pulmonary nodules at computed tomography (CT).

MATERIALS AND METHODS

CT images of 15 consecutive patients with (n = 13) or without (n = 2) pulmonary metastases were identified. Initial assessment by two thoracic radiologists provided the "actual" or reference reading. Subsequently, 10 radiologists [board certified radiologists (n = 4) or radiology residents (n = 6)] used different fixed cine frame rates for nodule detection. Within-subjects analysis of variance (ANOVA) was used to evaluate the data.

RESULTS

Eighty-nine nodules were identified by the thoracic radiologists (median 8, range 0-29 per patient; median diameter 9 mm, range 4-40 mm). There was a non-statistically significant trend to reduced accuracy at higher frame rates (p=0.113) with no statistically significant difference between experienced observers and residents (p = 0.79).

CONCLUSION

The accuracy of pulmonary nodule detection at higher cine frame rates is reduced, unrelated to observer experience.

Pediatric MDCT: towards assessing the diagnostic influence of dose reduction on the detection of small lung nodules

RATIONALE AND OBJECTIVES

The purpose of this study was to evaluate the effect of reduced tube current (dose) on lung nodule detection in pediatric multidetector array computed tomography (MDCT).

MATERIALS AND METHODS

The study included normal clinical chest MDCT images of 13 patients (aged 1-7 years) scanned at tube currents of 70 to 180 mA. Calibrated noise addition software was used to simulate cases as they would have been acquired at 70 mA (the lowest original tube current), 35 mA (50% reduction), and 17.5 mA (75% reduction). Using a validated nodule simulation technique, small lung nodules of 3 to 5 mm in diameter were inserted into the cases, which were then randomized and rated independently by three experienced pediatric radiologists for nodule presence on a continuous scale ranging from zero (definitely absent) to 100 (definitely present). The observer data were analyzed to assess the influence of dose on detection accuracy using the Dorfman-Berbaum-Mets method for multiobserver, multitreatment receiver-operating characteristic (ROC) analysis and the Williams trend test.

RESULTS

The areas under the ROC curves were 0.95, 0.91, and 0.92 at 70, 35, and 17.5 mA, respectively, with standard errors of 0.02 and interobserver variability of 0.02. The Dorfman-Berbaum-Mets method and the Williams trend test yielded P values for the effect of dose of .09 and .05, respectively.

CONCLUSION

Tube current (dose) has a weak effect on the detection accuracy of small lung nodules in pediatric MDCT. The effect on detection accuracy of a 75% dose reduction was comparable to interobserver variability, suggesting a potential for dose reduction.

Effect of slab thickness on the CT detection of pulmonary nodules: use of sliding thin-slab maximum intensity projection and volume rendering

OBJECTIVE

The objective of this study was to evaluate the detection rates of pulmonary nodules on CT as a function of slab thickness using sliding thin-slab maximum intensity projection (MIP) and volume rendering (VR).

SUBJECTS AND METHODS

Eighty-eight oncology patients (33 women, 55 men; mean age, 59 years; age range, 18-81 years) who routinely underwent chest CT examinations were prospectively included. Two radiologists independently evaluated each CT examination for the presence of pulmonary nodules using MIP and VR, with each image reconstructed using three different slab thicknesses (5, 8, 11 mm). The standard of reference was the maximum number of detected nodules, which were classified by localization and size, judged to be true-positives by a consensus panel. Interreader agreement was assessed by kappa value on a nodule-by-nodule basis. Sensitivities for both reconstruction techniques and for the three slab thicknesses were calculated using the proportion procedure for survey data with the patient as the primary sample unit and were compared using the Wilcoxon's signed rank test with Bonferroni correction for both readers separately.

RESULTS

One thousand fifty-eight true-positive nodules were detected. Interreader agreement was fair to moderate. Sensitivity for pulmonary nodules was superior for 8-mm MIP (reader 1, 84%; reader 2, 81%) and was significantly better than the sensitivities of all other tested techniques for both readers (p < 0.001 each) independent of nodule localization and size (except for one reader's analysis of 8-mm MIP versus 11-mm MIP for nodules > 8 mm). A higher sensitivity was achieved using MIP than VR.

CONCLUSION

MIP with a slab thickness of 8 mm is superior in the detection of pulmonary nodules to all other tested techniques.

[Usefulness of maximum intensity projections in low-radiation multislice CT lung cancer screening]

OBJECTIVE

To evaluate the diagnostic accuracy of non-overlapping 10-mm-thick axial maximum intensity projections (MIP) in the detection of pulmonary nodules in subjects participating in a lung cancer screening program (LCSP) using multislice computed tomography (MSCT) with a low dose of radiation.

MATERIAL AND METHODS

We evaluated 52 consecutive low-radiation MSCT studies in asymptomatic smokers included in an LCSP (1.25 mm axial images). Axial MIPs with 10mm slice thickness (30 images) were performed and evaluated retrospectively; readers were blind to the initial radiological report. All nodules detected were considered, regardless of their size or consistency. The standard of reference was determined by double reading and consensus for each nodule.

RESULTS

A total of 162 pulmonary nodules (mean size: 3.9 mm, sd: 1.7) were detected. MIP reconstruction detected 150 nodules (S = 92.6%). The initial radiological evaluation detected 108 nodules (S = 66.7%). MIP reconstruction detected 54 (33.3%) nodules that were not reported initially (mean size: 3.4 mm; sd: 1.2) but failed to detect 12 (7.4%) of the nodules reported initially (mean size: 2.91 mm; sd: 0.8). MIP detected all 35 nodules > or = 5 mm, (S =100), whereas the initial radiological evaluation only detected 27 (S = 77%). MIP reconstruction enabled more of the nodules to be detected than the 1.25-mm conventional axial slices (p < 0.01).

CONCLUSION

The introduction of non-overlapping 10-mm-thick axial MIP reconstructions in a low-radiation LCSP using MSCT enabled nodules more accurate and faster detection of pulmonary nodules in comparison with 1.25 mm conventional axial slices.

Postprocessing technique with MDCT data improves the accuracy of the detection of lung nodules

PURPOSE

The aim of this study was to determine whether postprocessing techniques could improve the accuracy of detecting lung nodules.

MATERIALS AND METHODS

A total of 154 segmented lung volumes of multidetector-row computed tomography (MDCT) data were the subject of the study. Lung nodules were present in 88 volumes and absent in 66 volumes. We prepared four groups: (1) 7- or 10-mm thick-section axial images; (2) 1-mm thin-section axial images; (3) sliding slab maximum intensity projection (MIP) images with a slab thickness of 15 mm; and (4) sliding slab volume rendering (VR) images with a slab thickness of 15 mm. Sixteen physicians reviewed each group in interactive cine mode. The observers' performance in the detection of lung nodule was evaluated by receiver operating characteristic (ROC) analysis.

RESULTS

The observers' performance of the MIP and VR groups was significantly better than in other two groups. There was no significant difference statistically between the thin and thick groups.

CONCLUSION

The detectability of lung nodules is improved with the use of sliding slab MIP and VR using thin-section image data. Thin-section volume data are essential for improving diagnostic accuracy, but observation of thin-section images without utilization of image-processing techniques dose not improve diagnostic accuracy.

Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection

This study aimed at evaluating the diagnostic benefits of maximum intensity projections (MIP) and a commercially available computed-assisted detection system (CAD) for the detection of pulmonary nodules on MDCT as compared with standard 1-mm images on lung cancer screening material. Thirty subjects were randomly selected from our database. Three radiologists independently reviewed three types of images: axial 1-mm images, axial MIP slabs, and CAD system detections. Two independent experienced chest radiologists decided which were true-positive nodules. Two hundred eighty-five nodules > or =1 mm were identified as true-positive by consensus of two independent chest radiologists. The detection rates of the three independent observers with 1-mm axial images were 22 +/- 4.8%, 30 +/- 5.3%, and 47 +/- 2.8%; with MIP: 33 +/- 5.4%, 39 +/- 5.7%, and 45 +/- 5.8%; and with CAD: 35 +/- 5.6%, 36 +/- 5.6%, and 36 +/- 5.6%. There was a reading technique effect on the observers' sensitivity for nodule detection: sensitivities with MIP were higher than with 1-mm images or CAD for all nodules (F-values = 0.046). For nodules > or =3 mm, readers' sensitivities were higher with 1-mm images or MIP than with CAD (p < 0.0001). CAD was the most and MIP the less time-consuming technique (p < 0.0001). MIP and CAD reduced the number of overlooked small nodules. As MIP is more sensitive and less time consuming than the CAD we used, we recommend viewing MIP and 1-mm images for the detection of pulmonary nodules.

Detección y caracterización del nódulo pulmonar por tomografía computarizada multicorte

Pulmonary nodules are a common finding in routine chest studies. Although there are no pathognomic clinical or radiological signs that enable the exact nature of a pulmonary nodule to be determined, the clinical context and the appropriate characterization of the pulmonary nodule make it possible to reach the correct diagnosis in most cases. This article discusses the most important aspects involved in the use of multislice computed tomography in the noninvasive detection and characterization of pulmonary nodules.

Pulmonary nodules: sensitivity of maximum intensity projection versus that of volume rendering of 3D multidetector CT data

PURPOSE

To prospectively compare maximum intensity projection (MIP) and volume rendering (VR) of multidetector computed tomographic (CT) data for the detection of small intrapulmonary nodules.

MATERIALS AND METHODS

This institutional review board-approved prospective study included 20 oncology patients (eight women and 12 men; mean age, 56 years +/- 16 [standard deviation]) who underwent clinically indicated standard-dose thoracic multidetector CT and provided informed consent. Transverse thin slabs of the chest (thickness, 7 mm; reconstruction increment, 3.5 mm) were created by using MIP and VR techniques to reconstruct CT data (collimation, 16 x 0.75 mm) and were reviewed in interactive cine mode. Mean, minimum, and maximum reading time per examination and per radiologist was documented. Three radiologists digitally annotated all nodules seen in a way that clearly determined their locations. The maximum number of nodules detected by the three observers and confirmed by consensus served as the reference standard. Descriptive statistics were calculated, with P < .05 indicating a significant difference. The Wilcoxon matched-pairs signed rank test and confidence intervals for differences between methods were used to compare the sensitivities of the two methods.

RESULTS

VR performed significantly better than MIP with regard to both detection rate (P < .001) and reporting time (P < .001). The superiority of VR was significant for all three observers and for nodules smaller than 11 mm in diameter and was pronounced for perihilar nodules (P = .023). Sensitivities achieved with VR ranged from 76.5% to 97.3%, depending on nodule size.

CONCLUSION

VR is the superior reading method compared with MIP for the detection of small solid intrapulmonary nodules.

How I Do It: CT Pulmonary Angiography

OBJECTIVE

The purpose of this article is to describe the techniques to improve motion artifacts, vascular enhancement, flow artifacts, body habitus image noise, vascular opacification in parenchymal lung disease, streak artifacts, and the indeterminate CT pulmonary angiogram. In addition, this article will illustrate the diagnostic criteria of acute and chronic pulmonary emboli.

CONCLUSION

Pulmonary embolism is the third most common acute cardiovascular disease, after myocardial infarction and stroke, and it leads to thousands of deaths each year because it often goes undetected. For the more than 25 years that the direct signs of pulmonary embolism have been available to the radiologist on CT, this noninvasive technique has produced a paradigm shift that has raised the standard of care for patients with this disease.

Solitary pulmonary nodule: detection and management

Pulmonary nodules are commonly detected at computed tomography (CT) of the chest. More than 95% are \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts,amssymb,amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n}{<-> linotext}{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $\le $ \end{document} 10 mm; of these more than 95% are benign. Visual detection of pulmonary nodules by human readers is suboptimal, particularly with small nodules \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts,amssymb,amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n}{<-> linotext}{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $\le $ \end{document} 10 mm. Computer-assisted detection can improve sensitivity and diagnostic confidence. Due to the high proportion of malignant lesions in nodules >10 mm immediate, often invasive work-up is required including contrast-enhanced dynamic CT, positron emission tomography (PET) or biopsy. However, in nodules \documentclass[12pt]{minimal} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts,amssymb,amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \DeclareFontFamily{T1}{linotext}{} \DeclareFontShape{T1}{linotext}{m}{n}{<-> linotext}{} \DeclareSymbolFont{linotext}{T1}{linotext}{m}{n} \DeclareSymbolFontAlphabet{\mathLINOTEXT}{linotext} \begin{document} $\le $ \end{document} 10 mm the high proportion of benign lesions requires a non-invasive work-up usually based on follow-up with unenhanced CT. Invasive procedures are only required for growing nodules. Stable nodules require further follow-up and decreasing nodules are considered benign.

Paradigms of Perception in Clinical Practice

Display strategies for medical images in radiology have evolved in tandem with the technology by which images are made. The close of the 20th century, nearly coincident with the 100th anniversary of the discovery of x-rays, brought radiologists to a new crossroad in the evolution of image display. The increasing availability, speed, and flexibility of computer technology can now revolutionize how images are viewed and interpreted. Radiologists are not yet in agreement regarding the next paradigm for image display. The possibilities are being explored systematically through the Society for Computer Applications in Radiology's Transforming the Radiological Interpretation Process initiative. The varied input of radiologists who work in a large variety of settings will enable new display strategies to best serve radiologists in the detection and quantification of disease. Considerations and possibilities for the future are presented in this paper.

A new software tool for removing, storing, and adding abnormalities to medical images for perception research studies

RATIONALE AND OBJECTIVES

Image perception studies have been difficult to perform using clinical images because of the problems associated with obtaining proven abnormalities and appropriate normal controls. The objective of this research was to develop and evaluate interactive software that allows the seamless removal, archiving and insertion of abnormal areas from computed tomography (CT) lung image sets for use in image perception research.

MATERIALS AND METHODS

The software tools for removing, archiving, and adding lesions are described in detail. The efficacy of the software to remove abnormal areas of lung CT studies was evaluated by having radiologists select the one altered image from a display of four. The software for adding lesions was evaluated by having radiologists classify displayed CT slices with lesions as real or artificial along with their confidence level.

RESULTS

Observers could not reliably detect when images had been altered by the software. In the lesion-removal experiment, the observers correctly identified the altered display in only 15.8 +/- 2.8 of 56 sets. In the lesion-add experiment, the observers correctly identified the artificially placed lesions in 38.2 +/- 3.9 of 77 sets. The frequency distribution of the correct responses did not differ from that expected from chance selection.

CONCLUSIONS

The results from both of these experiments demonstrate that radiologists could not distinguish between original and altered images. We conclude that this software can be used with volumetric CT lung images for creating normal control and target data sets for medical image perception research.

Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization

PURPOSE

To retrospectively evaluate whether a difference-image computer-aided detection (CAD) scheme can help radiologists detect peripheral lung cancers missed at low-dose computed tomography (CT).

MATERIALS AND METHODS

Institutional review board approval and informed patient and observer consent were obtained. Seventeen patients (eight men and nine women; mean age, 60 years) with a missed peripheral lung cancer and 10 control subjects (five men and five women; mean age, 63 years) without cancer at low-dose CT were included in an observer study. Fourteen radiologists were divided into two groups on the basis of different image display formats: Six radiologists (group 1) reviewed CT scans with a multiformat display, and eight radiologists (group 2) reviewed images with a "stacked" cine-mode display. The radiologists, first without and then with the CAD scheme, indicated their confidence level regarding the presence (or absence) of cancer and the most likely position of a lesion on each CT scan. Receiver operating characteristic (ROC) curves were calculated without and with localization to evaluate the observers' performance.

RESULTS

With the CAD scheme, the average area under the ROC curve improved from 0.763 to 0.854 for all radiologists (P = .002), from 0.757 to 0.862 for group 1 (P = .04), and from 0.768 to 0.848 for group 2 (P = .01). The average sensitivity in the detection of 17 cancers improved from 52% (124 of 238 observations) to 68% (163 of 238 observations) for all radiologists (P < .001), from 49% (50 of 102 observations) to 71% (72 of 102 observations) for group 1 (P = .02), and from 54% (74 of 136 observations) to 67% (91 of 136 observations) for group 2 (P = .006). The localization ROC curve also improved.

CONCLUSION

Lung cancers missed at low-dose CT were very difficult to detect, even in an observer study. The use of CAD, however, can improve radiologists' performance in the detection of these subtle cancers.

Small-Bowel Obstruction in a Phantom Model of ex Vivo Porcine Intestine: Comparison of PACS Stack and Tile Modes for CT Interpretation

PURPOSE

To compare computed tomographic (CT) image interpretation with picture archiving and communication systems (PACS) stack and tile modes for speed and accuracy of transition zone localization in small-bowel obstruction by using ex vivo porcine specimens.

MATERIALS AND METHODS

Twenty-five small-bowel obstruction phantom models made of ex vivo porcine intestines from a slaughterhouse were imaged at CT. One was used for observer training, and 24 were used for experimentation. At 20-cm intervals throughout the intestines, metallic markers were placed in the mesenteries immediately adjacent to bowel. One obstruction was made in each intestine, midway between markers, by ligating intestine with a 3-0 silk suture to simulate mechanical small-bowel obstruction. The lumen proximal to the ligation site was distended with air and a soybean oil-iodized oil mixture until at least two-thirds of the proximal intestine exceeded 2.0 cm in transverse diameter. Dilated segments were 310-550 cm in length. Soybean oil and a mixture of soybean and iodized oil were used to simulate differences in attenuation among bowel wall, intraluminal fluid, and extraluminal abdominal fat. Four experienced abdominal radiologists independently determined the transition zone by using stack mode (cine viewing of stacked images) and, at least 2 weeks later, tile mode (side-by-side image display). Accuracy and degree of error in counting markers were evaluated, and speed of interpretation was recorded. Statistical analysis was performed with the McNemar and Wilcoxon signed rank tests.

RESULTS

For all observers, accuracy of transition zone localization tended to be better with stack mode (63%-83% [15-20 phantoms]) than with tile mode (50%-63% [12-15 phantoms]), but the differences were not significant. For each observer, mean counting error was lower in stack mode (range, 0.96-2.48) than in tile mode (range, 1.74-3.22), with significance for three observers (P < .01, P < .01, and P = .04). Interpretation was significantly faster with stack mode by a factor of two to three for all observers (P < .01).

CONCLUSION

Stack mode evaluation for identification of the transition zone in obstructed small bowel is faster than evaluation with tile mode. Accuracy is not significantly different between modes, although there is a tendency toward better results with stack mode.

Value of axial and coronal maximum intensity projection (MIP) images in the detection of pulmonary nodules by multislice spiral CT: comparison with axial 1-mm and 5-mm slices

The purpose of this study was to investigate the diagnostic accuracy of non-overlapping 10-mm axial and coronal maximum intensity projections (MIP) in comparison with standard axial 1-mm and 5-mm slices in the detection of pulmonary nodules. Sixty patients with suspected nodules who underwent multislice spiral CT of the chest were evaluated. Axial 1-mm and 5-mm slices as well as non-overlapping 10-mm axial/coronal MIPs were interpreted independently by three blinded radiologists. After initial review, a retrospective consensus session was performed for agreement on final nodule counts using the axial 1-mm slices as gold standard. Small nodules of less than 5 mm in size were most accurately detected by the axial MIPs. Receiver operating characteristic (ROC) analysis of these small nodules showed that 5-mm slices were not capable of a statistically significant differentiation of nodules from other focal lesions in two observers (p=0.034 and p=0.012, respectively) whereas 1-mm slices and coronal/axial MIPs did allow a statistically significant differentiation in all observers (p<0.001). Nodules larger than 5 mm were equally well depicted with all modalities. Non-overlapping 10-mm axial MIPs improve the accuracy in the detection of small pulmonary nodules.

Impact of low-dose CT on lung cancer screening

Despite advances in therapy, the prognosis of lung cancer remains dismal due to the fact that most cases of lung cancer are diagnosed at advanced stages, when the chance of cure is poor. In cases detected at early stages prognosis is better. Unfortunately, early lung cancer usually causes no symptoms and is, consequently, rarely diagnosed. Therefore, screening for early asymptomatic lung cancer with diagnostic procedures appears promising particularly as risk factors for lung cancer are well known (cigarette smoking, occupational asbestos exposure and others) and screening could, therefore, focus on these risk groups. In the past, screening trials using analysis of sputum cytology and to some extent chest radiography have failed to demonstrate a reduction in lung-cancer mortality with screening, probably due to insufficient sensitivity of these tests for early lung cancer. During the last decade the introduction of spiral computed tomography (CT) has provided a technique with a much higher sensitivity for small lung cancers. Feasibility studies using low-radiation-dose CT demonstrated a high proportion of non-small-cell lung cancer at the initial examination (prevalence) with decreasing numbers of detected cancers at follow-up (incidence). The proportion of early-stage tumors was high both at prevalence and incidence examinations. The rate of invasive procedures for benign lesions was low; most indeterminate lesions could be classified with non-invasive diagnostic approaches. The proportion of interval cancers (cancers diagnosed by symptoms between two screening CT scans) was low. As, however, these one-arm feasibility trials are not appropriate to assess a potential mortality reduction through CT screening, prospective randomised multicenter trials were recently initiated in several countries to analyse the effect of CT screening on lung-cancer mortality.

Effect of temporal subtraction images on radiologists' detection of lung cancer on CT: results of the observer performance study with use of film computed tomography images

RATIONALE AND OBJECTIVES

To evaluate the effect of temporal subtraction images on the radiologists' detection of early primary lung cancer in computed tomography (CT) scans.

MATERIALS AND METHODS

Fourteen cases with primary lung cancer and 16 normal cases were used for this study from a database of low-dose CT images, which were obtained from a lung cancer screening program in Nagano, Japan. Images were obtained with a single-detector helical CT scanner using 10 mm collimation and 2:1 pitch. Each case had both previous and current CT scans. Temporal subtraction images were obtained by subtracting the warped previous images from the current images. Seven radiologists, including four attendings and three residents, provided their confidence levels for the presence or absence of lung cancers with use of film CT images without and with temporal subtraction images. Receiver operating characteristic analysis was used to compare their performance without and with temporal subtraction images.

RESULTS

The mean Az values (area under the receiver operating characteristic curve) of seven observers without and with temporal subtraction images were 0.868 and 0.930, respectively. Diagnostic accuracy was significantly improved by using temporal subtraction images (P = .007). Temporal subtraction images were especially useful when a nodule was present near the pulmonary hilum, where radiologists tended to overlook it.

CONCLUSION

The temporal subtraction technique can significantly improve the sensitivity and specificity for detection of lung cancer on CT scans.

Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT

The purpose of this study was to assess the effectiveness of double reading to increase the sensitivity of lung nodule detection at standard-dose (SDCT) and low-dose multirow-detector CT (LDCT). SDCT (100 mAs effective tube current) and LDCT (20 mAs) of nine patients with pulmonary metastases were obtained within 5 min using four-row detector CT. Softcopy images reconstructed with 5-mm slice thickness were read by three radiologists independently. Images with 1.25-mm slice thickness served as the gold standard. Sensitivity was assessed for single readers and combinations. The effectiveness of double reading was expressed as the increase of sensitivity. Average sensitivity for detection of 390 nodules (size 3.9+/-3.2 mm) for single readers was 0.63 (SDCT) and 0.64 (LDCT). Double reading significantly increased sensitivity to 0.74 and 0.79, respectively. No significant difference between sensitivity at SDCT and LDCT was observed. The percentage of nodules detected by all three readers concordantly was 52% for SDCT and 47% for LDCT. Although double reading increased the detection rate of pulmonary nodules from 63% to 74-79%, a considerable proportion of nodules remained undetected. No difference between sensitivities at LDCT and SDCT for detection of small nodules was observed.

[Radiological diagnosis of pulmonary metastases: imaging findings and diagnostic accuracy]

Pulmonary metastases typically present as mostly multiple and bilateral, well-defined, non-calcified pulmonary nodules with predominantly basal and peripheral location. Ill-defined, cavitating, calcified and endobronchial metastases are uncommon. In the absence of pathognomonic findings precise differentiation from other-even benign-pulmonary nodules is almost impossible. Demonstration of contrast enhancement at CT or MRI or evidence of growth at serial examinations support the diagnosis of pulmonary metastases. In uncertain cases percutaneous fine-needle aspiration or cutting needle biopsy will allow diagnosis with acceptable risk of complications and patient discomfort. The only relatively common complication of pneumothorax can and should be controlled by the interventional radiologist by aspiration or drainage.

Automatic detection of small lung nodules on CT utilizing a local density maximum algorithm

Increasingly, computed tomography (CT) offers higher resolution and faster acquisition times. This has resulted in the opportunity to detect small lung nodules, which may represent lung cancers at earlier and potentially more curable stages. However, in the current clinical practice, hundreds of such thin-sectional CT images are generated for each patient and are evaluated by a radiologist in the traditional sense of looking at each image in the axial mode. This results in the potential to miss small nodules and thus potentially miss a cancer. In this paper, we present a computerized method for automated identification of small lung nodules on multislice CT (MSCT) images. The method consists of three steps: (i) separation of the lungs from the other anatomic structures, (ii) detection of nodule candidates in the extracted lungs, and (iii) reduction of false-positives among the detected nodule candidates. A three-dimensional lung mask can be extracted by analyzing density histogram of volumetric chest images followed by a morphological operation. Higher density structures including nodules scattered throughout the lungs can be identified by using a local density maximum algorithm. Information about nodules such as size and compact shape are then incorporated into the algorithm to reduce the detected nodule candidates which are not likely to be nodules. The method was applied to the detection of computer simulated small lung nodules (2 to 7 mm in diameter) and achieved a sensitivity of 84.2% with, on average, five false-positive results per scan. The preliminary results demonstrate the potential of this technique for assisting the detection of small nodules from chest MSCT images.

Metastases of colorectal carcinoma: comparison of soft- and hard-copy helical CT interpretation

PURPOSE

To compare soft- and hard-copy computed tomographic (CT) image interpretation with regard to evaluation time and detection rates for hepatic and extrahepatic colorectal metastases in candidates for liver surgery.

MATERIALS AND METHODS

In 20 patients with a history of colorectal carcinoma, two radiologists independently evaluated CT data sets. Focal hepatic lesions were characterized as benign or malignant by using a five-point scale. In each patient, soft-copy readouts and hard-copy printouts were compared for nonenhanced hepatic, contrast material-enhanced hepatic, and contrast-enhanced extrahepatic data sets. A stopwatch was used to document evaluation time. Ninety-two hepatic metastases and six extrahepatic metastatic recurrences were detected with the standard of reference--surgical, intraoperative ultrasonographic, and histologic findings.

RESULTS

Both observers evaluated the contrast-enhanced hepatic data set significantly faster (P =.026 and.009) by using soft-copy readouts. The contrast-enhanced extrahepatic data set was also evaluated significantly faster (P =.010 and.006) with soft-copy readouts. Detection of hepatic and extrahepatic tumor with soft-copy readouts is not significantly superior to that with hard copies. Detection rates of hepatic metastases for nonenhanced and contrast-enhanced CT for both observers ranged from 50%-80% (46-74 of 92) for soft-copy readouts and 46%-75% (42-69 of 92) for hard copies. Interobserver agreement was highest for contrast-enhanced soft-copy readouts for hepatic metastases.

CONCLUSION

Soft-copy readouts of contrast-enhanced CT data sets for the detection of hepatic metastases and extrahepatic metastatic recurrences were evaluated significantly faster than were hard copies, with at least equal sensitivity and with excellent interobserver agreement.

Automatic detection of small lung nodules on CT utilizing a local density maximum algorithm

Increasingly, computed tomography (CT) offers higher resolution and faster acquisition times. This has resulted in the opportunity to detect small lung nodules, which may represent lung cancers at earlier and potentially more curable stages. However, in the current clinical practice, hundreds of such thin-sectional CT images are generated for each patient and are evaluated by a radiologist in the traditional sense of looking at each image in the axial mode. This results in the potential to miss small nodules and thus potentially miss a cancer. In this paper, we present a computerized method for automated identification of small lung nodules on multislice CT (MSCT) images. The method consists of three steps: (i) separation of the lungs from the other anatomic structures, (ii) detection of nodule candidates in the extracted lungs, and (iii) reduction of false-positives among the detected nodule candidates. A three-dimensional lung mask can be extracted by analyzing density histogram of volumetric chest images followed by a morphological operation. Higher density structures including nodules scattered throughout the lungs can be identified by using a local density maximum algorithm. Information about nodules such as size and compact shape are then incorporated into the algorithm to reduce the detected nodule candidates which are not likely to be nodules. The method was applied to the detection of computer simulated small lung nodules (2 to 7 mm in diameter) and achieved a sensitivity of 84.2% with, on average, five false-positive results per scan. The preliminary results demonstrate the potential of this technique for assisting the detection of small nodules from chest MSCT images.

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

A method for changing the tube current during helical scanning was applied to low-dose computed tomography (CT) in the lung. The changing method resulted in significant equalization of image noise in various lung sections compared with that at scanning with constant tube current. Detectability of nodules was equivalent between 60 mA and the changing method, whereas degradation occurred at 20 mA. This method seems feasible for the low-dose CT of lung cancer screening.

Incremental benefit of maximum-intensity-projection images on observer detection of small pulmonary nodules revealed by multidetector CT

OBJECTIVE

Our purpose was to assess the incremental effect of maximum-intensity-projection (MIP) image processing on the ability of various observers to detect small (<1 cm in diameter) central and peripheral lung nodules revealed by multidetector CT.

MATERIALS AND METHODS

We retrospectively identified 25 patients with metastatic disease, each having from two to nine nodules that were 3-9 mm in diameter. Two senior and three junior reviewers interpreted all images on a workstation. The observers first reviewed axial images (3.75-mm collimation, 3-mm reconstruction interval, multidetector acquisition) in cine and sequential fashion and recorded the size, lobe, and central or peripheral (within 1 cm of the edge of lung) location of each nodule. MIP images (10-mm slab, 8-mm interval) were then reviewed, and additional nodules detected were recorded. Final counts were established by consensus.

RESULTS

The reviewers found 122 nodules (71 peripheral, 51 central) in the 25 patients. The addition of MIP slabs significantly enhanced reviewer detection of central nodules (p < 0.001) and junior reviewer detection of peripheral nodules (p < 0.001). MIP slabs also reduced the effects of reviewer experience, particularly for peripheral nodules.

CONCLUSION

MIP processing reduces the number of overlooked small nodules, particularly in the central lung. Observer nodule detection remains imperfect even when lesions are clearly depicted on images.

The solitary pulmonary nodule

The radiologic evaluation of the solitary pulmonary nodule (SPN) is a common diagnostic dilemma. Although available clinical data and findings on conventional radiographs are important components in determining the imaging approach to the SPN, evaluation with CT often is necessary for detailed evaluation. This article reviews the radiologist's approach to the evaluation of the SPN, with a particular focus on the role of thin-section CT for morphologic and density analysis. The relative use of contrast-enhanced CT and nuclear medicine, particularly positron emission tomography, in detecting nodule enhancement is discussed. If the use of low-dose helical CT for screening for early lung cancer in the form of a SPN becomes widespread practice, it is likely that radiologists will encounter an increasing number of smaller SPNs in the near future.

Cine viewing of abdominal CT

A few studies have been reported that CT cine viewing on the CRT is superior to film-based viewing of CT images (Seltzer et al., Radiology 197 (1994) 119; Bonaldi et al., Am. J. Roentgenol. 170 (1998) 373; Tillich et al., Am. J. Roentgenol. 169 (1997) 1611). The purpose of our study is to know how to use cine viewing of abdominal CT. Thirty CT studies on the abdomen with both precontrast and postcontrast images were examined. The suitable rate of cine viewing ranged from 1 to 6 frames per second according to the size, the contrast and the complexity of the anatomical structures, and the slice thickness. For small or complex structures, checking each image might be required to know the full detail of them. Positional sorting among multiphase images, which is followed by consecutive display of a precontrast image, postcontrast early and late phase images at one position and so on, is useful to see the dynamic pattern of enhancement of the anatomical structures. However, there was no significant difference between cine viewing and film-based viewing concerning both the detectability of the anatomical structures and the conspicuity of enhancement of the liver and the pancreas, so that cine viewing might be an alternative to film-based viewing for CT diagnosis of the abdomen.

Lung cancer screening: minimum tube current required for helical CT

PURPOSE

To investigate the minimum tube current required for helical computed tomography (CT) for lung cancer screening.

MATERIALS AND METHODS

Thirty helical scans of the lung were obtained at effective tube currents of 50, 30, 20, 18, 12, 10, and 6 mAs in seven healthy volunteers. Computer-generated nodules 6 mm in diameter that showed ground-glass opacity were superimposed on the images. The image quality and detectability of nodules were evaluated subjectively by six observers. The SDs of measured CT numbers were calculated. The results were analyzed according to location in the lung.

RESULTS

Compared with the subjective quality of images obtained at 50 mAs, the subjective quality of images obtained at 20 mAs was not significantly different. The detectability of nodules was not significantly degraded by reducing the tube current to 20 mAs in the upper zone of the lung, to 12 mAs in the middle zone, or to 18 mAs in the lower zone. The SDs at the apex and base of the lung were larger than those at other levels, and the difference became greater as the dose was reduced.

CONCLUSION

The minimum tube current required for screening helical CT differs for different locations in the lung. An ideal CT protocol for the lung should permit the tube current to be changed during helical scanning.