Dual-energy digital subtraction chest radiography: Technical considerations

Whitman, Gary J.; Niklason, Loren T.; Pandit, Meenakshi; Oliver, L. Christine; Atkins, Elisha H.; Kinnard, Olga; Alexander, A.; Weiss, Michelle K.; Sunku, Kavitha; Schulze, Eric; Greene, Reginald E.

doi:10.1067/mdr.2002.122856

Cited by 30 publications

(15 citation statements)

References 10 publications

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“…However, the value of the dual-energy technique remains under vigorous discussion in the literature, as different results have been published. In contrast to our own results, several reports have been published claiming that the dual-energy technique added to conventional chest images significantly improves the detection of pulmonary nodules [15][16][17][18]. Both single as well as dual-exposure dual-energy techniques have been proposed for chest radiography [16,19,20].…”

Section: Discussioncontrasting

confidence: 78%

CsI-detector-based dual-exposure dual energy in chest radiography for lung nodule detection: results of an international multicenter trial

et al. 2008

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To assess both sensitivity and specificity of digital chest radiography alone and in conjunction with dual-exposure dual-energy chest radiography for the detection and classification of pulmonary nodules. One hundred patients with a total of 149 lung nodules (3-45 mm; median, 11 mm) confirmed by CT were included in this study. Dual-exposure dual-energy chest radiographies of each patient were obtained using a CsI detector system. Experienced board-certified chest radiologists from four different medical centers in Europe reviewed standard chest radiographs alone and in conjunction with dual-energy images blinded and in random order. The reviewers rated the probability of presence, calcification and malignancy of all lung nodules on a five-point rating scale. Lesions detected were identified by applying a specific coordinate system to enable precise verification by the study leader. A receiver-operating characteristic (ROC) analysis was performed. In addition to the 149 true-positive CT proven lesions, 236 false-positive lung nodules were described in digital chest radiographies in conjunction with dual-energy chest radiographies. The cumulative sensitivity of chest radiography in conjunction with dual energy was 43%, specificity was 55%. For digital radiography alone, sensitivity was 35% and specifity was 83%. For the dual energy system, positive predictive value was 58%, and negative predictive value was 66% compared to the digital radiography with a positive predictive value of 59% and a negative predictive value of 65%. Areas under the curve in a ROC analysis resulted in 0.631 (95% confidence interval =0.61 to 0.65) for radiography with dual energy and 0.602 (95% confidence interval =0.58 to 0.63) for digital radiography alone. This difference was not statistically significant. For the detection of lesion calcification or the determination of malignancy, ROC analysis also failed to show significant differences. CsI-based flat-panel dual-exposure dual-energy imaging added to standard chest radiography did not show statistically significant improvement for the detection of pulmonary nodules, nor the identification of calcifications, nor the determination of malignancy.

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Section: Discussioncontrasting

confidence: 78%

CsI-detector-based dual-exposure dual energy in chest radiography for lung nodule detection: results of an international multicenter trial

et al. 2008

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“…DE imaging enhances visualization of soft-tissue abnormalities, such as lung tumours, in chest radiographs by taking advantage of the different degrees to which tissues attenuate high-and low-energy photons. [30][31][32][33][34][35][36][37][38][39][40][41][42] The DE process involves obtaining two different radiographs, one at low energy (such as 60 kVp) and one at high energy (such as 120 kVp). Using these images, a weighted logarithmic subtraction is performed that removes obscuring bony anatomy (ribs and vertebral bodies), thus creating a third image that highlights soft tissue, such as lung tumours.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

Block

Patel

Sürücü

et al. 2016

The British Journal of Radiology

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Objective: To evaluate a template-based matching algorithm on single-energy (SE) and dual-energy (DE) radiographs for markerless localization of lung tumours. Methods: A total of 74 images from 17 patients with Stages IA-IV lung cancer were considered. At the time of radiotherapy treatment, gated end-expiration SE radiographs were obtained at 60 and 120 kVp at different gantry angles (33°anterior and 41°oblique), from which soft-tissue-enhanced DE images were created. A template-based matching algorithm was used to localize individual tumours on both SE and DE radiographs. Tumour centroid co-ordinates obtained from the template-matching software on both SE and DE images were compared with co-ordinates defined by physicians.Results: The template-based matching algorithm was able to successfully localize the gross tumor volume within 5 mm on 70% (52/74) of the SE images vs 91% (66/ 74) of the DE images (p , 0.01). The mean vector differences between the co-ordinates of the template matched by the algorithm and the co-ordinates of the physician-defined ground truth were 3.2 6 2.8 mm for SE images vs 2.3 6 1.7 mm for DE images (p 5 0.03). Conclusion: Template-based matching on DE images was more accurate and precise than using SE images. Advances in knowledge: This represents, to the authors' knowledge, the largest study evaluating template matching on clinical SE and DE images, considering not only anterior gantry angles but also oblique angles, suggesting a novel lung tumour matching technique using DE subtraction that is reliable, accurate and precise.

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“…For the DE subtraction technique (9)(10)(11) , the same ROI was scanned using two different X-ray energy spectra to obtain two sets of images for subtraction. By analyzing the changes in the CT values of different tissues resulting from the use of different X-ray energies, the tissue densities can be distinguished.…”

Section: Discussionmentioning

confidence: 99%

Clinical applications of virtual, non-contrast head images derived from dual-source, dual-energy cerebrovascular computed tomography angiography

Han

Xie

2016

IJRR

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Background: This study set out to evaluate the u lity of cerebrovascular virtual non-contrast (VNC) scans. Materials and Methods: Conven onal non-contrast (CNC) and dual-energy computed tomography angiography (DE-CTA) head scans were conducted on 100 subjects, of which 46 were normal, 15 had parenchymal hematomas of the brain, 13 had ischemic infarc on, 22 had tumors, and 4 had calcified lesions. VNC images were extracted from the DE-CTA head scans by post-processing. The true (or conven onal) and VNC images were compared in terms of the mean CT a.enua on value and signal-to-noise ra o (SNR) of the cerebral parenchyma, the image quality, the lesion detec on sensi vity, and the radia on exposure level. Results: The image quali es of the CNC and VNC scans were (4.95 ± 0.22) points and (3.94 ± 0.24) points (t = 31.18, P < 0.05), the mean CT values for the CNC and VNC images were (34.6 ± 2.44) and (28.6 ± 5.40) HU (t = 10.126, P < 0.05), the SNRs were (9.45 ± 1.26) and (6.87 ± 1.77), and the HU for white ma.er was (t = 11.859, P<0.05), respec vely. The effec ve radia on doses from the DE-CTA head scans and the conven onal non-contrast scans were (8.55 ± 0.57) mSv and (9.41 ± 1.00) mSv, respec vely. No significant difference in the lesion detec on sensi vi es was observed between the CNC and VNC scans, except for ny calcified lesions, which could not be iden fied by a VNC scan. Conclusion: VNC and contrast-enhanced images could be obtained from DE-CTA head scans and could aid in the diagnosis of cerebral lesions. The radia on dose from the VNC scan was less than that from the CNC scan.

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Dual-energy digital subtraction chest radiography: Technical considerations

Cited by 30 publications

References 10 publications

CsI-detector-based dual-exposure dual energy in chest radiography for lung nodule detection: results of an international multicenter trial

CsI-detector-based dual-exposure dual energy in chest radiography for lung nodule detection: results of an international multicenter trial

Evaluation of a template-based algorithm for markerless lung tumour localization on single- and dual-energy kilovoltage images

Clinical applications of virtual, non-contrast head images derived from dual-source, dual-energy cerebrovascular computed tomography angiography

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