Objectives This study sought to determine the diagnostic accuracy of 64-slice computed tomographic coronary angiography (CTCA) to detect or rule out significant coronary artery disease (CAD). ...Background CTCA is emerging as a noninvasive technique to detect coronary atherosclerosis. Methods We conducted a prospective, multicenter, multivendor study involving 360 symptomatic patients with acute and stable anginal syndromes who were between 50 and 70 years of age and were referred for diagnostic conventional coronary angiography (CCA) from September 2004 through June 2006. All patients underwent a nonenhanced calcium scan and a CTCA, which was compared with CCA. No patients or segments were excluded because of impaired image quality attributable to either coronary motion or calcifications. Patient-, vessel-, and segment-based sensitivities and specificities were calculated to detect or rule out significant CAD, defined as ≥50% lumen diameter reduction. Results The prevalence among patients of having at least 1 significant stenosis was 68%. In a patient-based analysis, the sensitivity for detecting patients with significant CAD was 99% (95% confidence interval CI: 98% to 100%), specificity was 64% (95% CI: 55% to 73%), positive predictive value was 86% (95% CI: 82% to 90%), and negative predictive value was 97% (95% CI: 94% to 100%). In a segment-based analysis, the sensitivity was 88% (95% CI: 85% to 91%), specificity was 90% (95% CI: 89% to 92%), positive predictive value was 47% (95% CI: 44% to 51%), and negative predictive value was 99% (95% CI: 98% to 99%). Conclusions Among patients in whom a decision had already been made to obtain CCA, 64-slice CTCA was reliable for ruling out significant CAD in patients with stable and unstable anginal syndromes. A positive 64-slice CTCA scan often overestimates the severity of atherosclerotic obstructions and requires further testing to guide patient management.
Objectives
To benchmark the performance of state-of-the-art computer-aided detection (CAD) of pulmonary nodules using the largest publicly available annotated CT database (LIDC/IDRI), and to show ...that CAD finds lesions not identified by the LIDC’s four-fold double reading process.
Methods
The LIDC/IDRI database contains 888 thoracic CT scans with a section thickness of 2.5 mm or lower. We report performance of two commercial and one academic CAD system. The influence of presence of contrast, section thickness, and reconstruction kernel on CAD performance was assessed. Four radiologists independently analyzed the false positive CAD marks of the best CAD system.
Results
The updated commercial CAD system showed the best performance with a sensitivity of 82 % at an average of 3.1 false positive detections per scan. Forty-five false positive CAD marks were scored as nodules by all four radiologists in our study.
Conclusions
On the largest publicly available reference database for lung nodule detection in chest CT, the updated commercial CAD system locates the vast majority of pulmonary nodules at a low false positive rate. Potential for CAD is substantiated by the fact that it identifies pulmonary nodules that were not marked during the extensive four-fold LIDC annotation process.
Key Points
•
CAD systems should be validated on public, heterogeneous databases.
•
The LIDC/IDRI database is an excellent database for benchmarking nodule CAD.
•
CAD can identify the majority of pulmonary nodules at a low false positive rate.
•
CAD can identify nodules missed by an extensive two-stage annotation process.
CT pulmonary angiography (CTPA) has been suggested by the Fleischner society as the first test following a negative leg ultrasound in pregnant patients with suspected pulmonary embolism. This ...editorial discusses the use of CTPA as a diagnostic tool in pregnant women and comments on the need for specifically adapting CT protocols during pregnancy in the light of new research describing a substantial number of non-diagnostic examinations in pregnant women if routine scanning protocols are used for CTA of the pulmonary arteries. Potential reasons for these high numbers of insufficient examinations are physiological changes occurring during pregnancy that lead to a hyperdynamic circulation, which reduces average enhancement of the pulmonary vasculature. In addition, there are possible breathing-related effects that include an increased risk for Valsalva manoeuvre with devastating effects for pulmonary vascular enhancement. Techniques to overcome these problems are discussed: bolus triggering with short start delays, high flow rates or high contrast medium concentration, preferential use of fast CT systems and the use of low kVp CT techniques. CT data acquisition during deep inspiration should be avoided and shallow respiration may be considered as an alternative to suspended breathing in this patient group. All these factors can contribute to optimization of the quality of pulmonary CTA in pregnant patients. It is time now to adapt our protocols and provide optimum care for this sensitive patient group.
Purpose
Model-based iterative reconstruction (MBIR) yields higher spatial resolution and a lower image noise than conventional reconstruction methods. We hypothesized that thin-slice MBIR designed ...for brain CT could improve the detectability of acute ischemic stroke in the middle cerebral artery (MCA) territory.
Methods
Included were 41 patients with acute ischemic stroke in the MCA territory; they were seen at 4 medical centers. The controls were 39 subjects without acute stroke. Images were reconstructed with hybrid IR and with MBIR designed for brain CT at slice thickness of 2 mm. We measured the image noise in the ventricle and compared the contrast-to-noise ratio (CNR) in the ischemic lesion. We analyzed the ability of reconstructed images to detect ischemic lesions using receiver operating characteristics (ROC) analysis; 8 observers read the routine clinical hybrid IR with 5 mm-thick images, while referring to 2 mm-thick hybrid IR images or MBIR images.
Results
The image noise was significantly lower on MBIR- than hybrid IR images (1.2 vs. 3.4,
p
< 0.001). The CNR was significantly higher with MBIR than hybrid IR (6.3 vs. 1.6,
p
< 0.001). The mean area under the ROC curve was also significantly higher on hybrid IR plus MBIR than hybrid IR (0.55 vs. 0.48,
p
< 0.036). Sensitivity, specificity, and accuracy were 41.2%, 88.8%, and 65.7%, respectively, for hybrid IR; they were 58.8%, 86.1%, and 72.9%, respectively, for hybrid IR plus MBIR.
Conclusion
The additional thin-slice MBIR designed for brain CT may improve the detection of acute MCA stroke.
Fat surrounding coronary arteries might aggravate coronary artery disease (CAD). We investigated the relation between epicardial adipose tissue (EAT) and pericoronary fat and coronary atherosclerosis ...and coronary artery calcium (CAC) in patients with suspected CAD and whether this relation is modified by total body weight. This was a cross-sectional study of 128 patients with angina pectoris (61 ± 6 years of age) undergoing coronary angiography. EAT volume and pericoronary fat thickness were measured with cardiac computed tomography. Severity of coronary atherosclerosis was assessed by the number of stenotic (≥50%) coronary vessels; extent of CAC was determined by the Agatston score. Patients were stratified for median total body weight (body mass index BMI 27 kg/m2 ). Overall, EAT and pericoronary fat were not associated with severity of coronary atherosclerosis and extent of CAC. In patients with low BMI, those with multivessel disease had increased EAT volume (100 vs 67 cm3 , p = 0.04) and pericoronary fat thickness (9.8 vs 8.4 mm, p = 0.06) compared with those without CAD. Also, patients with severe CAC had increased EAT volume (108.0 vs 69 cm3 , p = 0.02) and pericoronary fat thickness (10.0 vs 8.2 mm, p value = 0.01) compared with those with minimal/absent CAC. In conclusion, EAT and pericoronary fat were not associated with severity of coronary atherosclerosis and CAC in patients with suspected CAD. However, in those with low BMI, increased EAT and pericoronary fat were related to more severe coronary atherosclerosis and CAC. Fat surrounding coronary arteries may be involved in the process of coronary atherosclerosis, although this is different for patients with low and high BMIs.
Objectives
To compare the PanCan model, Lung-RADS and the 1.2016 National Comprehensive Cancer Network (NCCN) guidelines for discriminating malignant from benign pulmonary nodules on baseline ...screening CT scans and the impact diameter measurement methods have on performances.
Methods
From the Danish Lung Cancer Screening Trial database, 64 CTs with malignant nodules and 549 baseline CTs with benign nodules were included. Performance of the systems was evaluated applying the system's original diameter definitions: D
longest-C
(PanCan), D
meanAxial
(NCCN), both obtained from axial sections, and D
mean3D
(Lung-RADS). Subsequently all diameter definitions were applied uniformly to all systems. Areas under the ROC curves (AUC) were used to evaluate risk discrimination.
Results
PanCan performed superiorly to Lung-RADS and NCCN (AUC 0.874 vs. 0.813, p = 0.003; 0.874 vs. 0.836, p = 0.010), using the original diameter specifications. When uniformly applying D
longest-C
, D
mean3D
and D
meanAxial
, PanCan remained superior to Lung-RADS (p < 0.001 – p = 0.001) and NCCN (p < 0.001 – p = 0.016). Diameter definition significantly influenced NCCN’s performance with D
longest-C
being the worst (D
longest-C
vs. D
mean3D
, p = 0.005; D
longest-C
vs. D
meanAxial
, p = 0.016).
Conclusions
Without follow-up information, the PanCan model performs significantly superiorly to Lung-RADS and the 1.2016 NCCN guidelines for discriminating benign from malignant nodules. The NCCN guidelines are most sensitive to nodule size definition.
Key Points
•
PanCan model outperforms Lung
-
RADS and 1.2016 NCCN guidelines in identifying malignant pulmonary nodules
.
•
Nodule size definition had no significant impact on Lung
-
RADS and PanCan model
.
•
1.2016 NCCN guidelines were significantly superior when using mean diameter to longest diameter
.
•
Longest diameter achieved lowest performance for all models
.
•
Mean diameter performed equivalently when derived from axial sections and from volumetry
.
Normalized emphysema score is a protocol-robust CT biomarker of mortality. We aimed to improve mortality prediction by including the emphysema score progression rate-its change over time-into the ...models.
CT scans from 6000 National Lung Screening Trial CT arm participants were included. Of these, 1810 died (445 lung cancer-specific). The remaining 4190 survivors were sampled with replacement up to 24432 to approximate the full cohort. Three overlapping subcohorts were formed which required participants to have images from specific screening rounds. Emphysema scores were obtained after resampling, normalization, and bullae cluster analysis of the original images. Base models contained solely the latest emphysema score. Progression models included emphysema score progression rate. Models were adjusted by including baseline age, sex, BMI, smoking status, smoking intensity, smoking duration, and previous COPD diagnosis. Cox proportional hazard models predicting all-cause and lung cancer mortality were compared by calculating the area under the curve per year follow-up.
In the subcohort of participants with baseline and first annual follow-up scans, the analysis was performed on 4940 participants (23227 after resampling). Area under the curve for all-cause mortality predictions of the base and progression models 6 years after baseline were 0.564 (0.564 to 0.565) and 0.569 (0.568 to 0.569) when unadjusted, and 0.704 (0.703 to 0.704) to 0.705 (0.704 to 0.705) when adjusted. The respective performances predicting lung cancer mortality were 0.638 (0.637 to 0.639) and 0.643 (0.642 to 0.644) when unadjusted, and 0.724 (0.723 to 0.725) and 0.725 (0.725 to 0.726) when adjusted.
Including emphysema score progression rate into risk models shows no clinically relevant improvement in mortality risk prediction. This is because scan normalization does not adjust for an overall change in lung density. Adjusting for changes in smoking behavior is likely required to make this a clinically useful measure of emphysema progression.
The original version of this article, published on 10 February 2019, unfortunately contained a mistake. The axes of the graphs in Fig. 3 are incorrect. The correct figure is given below. Therefore, ...the last two sentences in “Results,” section “Noise,” should read: “The peak frequency of the HR and SHR was
0.21 lp/mm
. For the NR mode and the MDCT, the peak frequencies were
0.17 lp/mm
and
0.21 lp/mm
, respectively.”
The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient ...exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems.
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