Conventional chest radiography vs dual-energy computed radiography in the detection and characterization of pulmonary nodules.

Kelcz, Frederick; Zink, Frank E.; Peppler, W.; Kruger, David G.; Ergun, David L.; Mistretta, Charles A.

doi:10.2214/ajr.162.2.8310908

Cited by 84 publications

(66 citation statements)

References 28 publications

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“…Dual-energy chest radiographs can be obtained by either a rapid sequence of two exposures, each at a different energy level [e.g., one at 60-80 kV and the other at 110-150 kV] [55]- [58], or a single exposure that is detected by two receptor plates separated by a filter for obtaining images at two different energy levels [44], [48], [49]. Dual-energy soft-tissue images can improve the detection of focal soft-tissue opacities, such as lung nodules, that may be partly obscured by overlying ribs or clavicles [29], [30], [59]. In spite of the advantages, a very limited number of hospitals use radiography systems with dual-energy subtraction, because specialized equipment for obtaining dual-energy X-ray exposures is required.…”

Section: Discussionmentioning

confidence: 99%

“…This results in lowering the sensitivity as well as the specificity of a CAD scheme. Because nodules overlapping with ribs and clavicles were reported to be difficult for radiologists to observe [29], [30], detection of such nodules is important for CAD schemes. Therefore, the suppression of ribs and clavicles in chest radiographs would be potentially useful for improving radiologists' detection accuracy as well as the CAD performance.…”

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confidence: 99%

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Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)

Suzuki

Abé

MacMahon

et al. 2006

IEEE Trans. Med. Imaging

217

157

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Abstract-When lung nodules overlap with ribs or clavicles in chest radiographs, it can be difficult for radiologists as well as computer-aided diagnostic (CAD) schemes to detect these nodules. In this paper, we developed an image-processing technique for suppressing the contrast of ribs and clavicles in chest radiographs by means of a multiresolution massive training artificial neural network (MTANN). An MTANN is a highly nonlinear filter that can be trained by use of input chest radiographs and the corresponding "teaching" images. We employed "bone" images obtained by use of a dual-energy subtraction technique as the teaching images. For effective suppression of ribs having various spatial frequencies, we developed a multiresolution MTANN consisting of multiresolution decomposition/composition techniques and three MTANNs for three different-resolution images. After training with input chest radiographs and the corresponding dual-energy bone images, the multiresolution MTANN was able to provide "bone-image-like" images which were similar to the teaching bone images. By subtracting the bone-image-like images from the corresponding chest radiographs, we were able to produce "soft-tissue-image-like" images where ribs and clavicles were substantially suppressed. We used a validation test database consisting of 118 chest radiographs with pulmonary nodules and an independent test database consisting of 136 digitized screen-film chest radiographs with 136 solitary pulmonary nodules collected from 14 medical institutions in this study. When our technique was applied to nontraining chest radiographs, ribs and clavicles in the chest radiographs were suppressed substantially, while the visibility of nodules and lung vessels was maintained. Thus, our image-processing technique for rib suppression by means of a multiresolution MTANN would be potentially useful for radiologists as well as for CAD schemes in detection of lung nodules on chest radiographs.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)

Suzuki

Abé

MacMahon

et al. 2006

IEEE Trans. Med. Imaging

217

157

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“…Previous authors have indicated that overlying bone structures may obscure pulmonary pathology [1,2]. Dual-energy (DE) techniques are one possible method to reduce this source of anatomical noise.…”

Section: Introductionmentioning

confidence: 99%

“…In previous studies, DE techniques employing storage phosphor plates or phosphor/photodiode detectors have proven advantages in the detection of solitary pulmonary nodules and chest calcifications [2,4,5]. Despite these promising results, these systems have not gained wide acceptance because of inconsistent image quality or difficulties in handling or processing of the images [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

Clinical results of CsI-detector-based dual-exposure dual energy in chest radiography

et al. 2003

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The aim of this study was to compare the sensitivity and specificity of digital chest radiography alone with digital chest radiography combined with dual-energy chest radiography in the detection of small non-calcified pulmonary nodules. Standard and dual-energy radiographs were obtained with a flat-panel digital chest system. Four radiologists reviewed digital posteroanterior chest radiographs in random order either alone or in conjunction with dual-energy soft tissue and bone images. Twenty patients with a total of 59 pulmonary nodules (median 0.5 cm, range 0.3-2.5 cm) confirmed by computed tomography (HU < or =100) were included. A level of confidence for each diagnosis was documented using a rating scale of 1-5. Brunner and Langer's test was performed for statistical analysis. Subgroup analysis was performed for nodules greater than 1 cm, 1-0.5 cm, and <0.5 cm. For posteroanterior chest radiography, sensitivity was 33%, positive predictive value 83%, specificity 81%, and negative predictive value 30%. Review in conjunction with dual-energy images resulted in a sensitivity of 42%, positive predictive value 88%, specificity 85%, and negative predictive value 34%. The increase of nodule detection overall as well as for different size categories was significant (p<0.05). The increase of the confidence level rating was also significant (p<0.001). Dual energy added to standard posteroanterior chest radiography significantly improves the sensitivity, specificity, and confidence in detection of small non-calcified pulmonary nodules.

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“…Prior to the development of tomosynthesis, dual-energy (DE) imaging was used as an improvement over conventional chest radiography for the detection and classification of pulmonary nodules by reducing the visual clutter associated with the ribs and providing information on patterns of nodule calcification (24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34). In general, however, DE imaging has shown more modest THORACIC IMAGING: Multi-Institutional Evaluation of Pulmonary Nodules Dobbins et al observers freely marked the location of lesions without cues such as designated regions of interest, and they used the measurement tool to draw a line through the center of the nodule to indicate its diameter.…”

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confidence: 99%

Multi-Institutional Evaluation of Digital Tomosynthesis, Dual-Energy Radiography, and Conventional Chest Radiography for the Detection and Management of Pulmonary Nodules

Dobbins

McAdams

Sabol³

et al. 2017

Radiology

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Purpose:To conduct a multi-institutional, multireader study to compare the performance of digital tomosynthesis, dual-energy (DE) imaging, and conventional chest radiography for pulmonary nodule detection and management. Materials and Methods:In this binational, institutional review board-approved, HIPAAcompliant prospective study, 158 subjects (43 subjects with normal findings) were enrolled at four institutions. Informed consent was obtained prior to enrollment. Subjects underwent chest computed tomography (CT) and imaging with conventional chest radiography (posteroanterior and lateral), DE imaging, and tomosynthesis with a flat-panel imaging device. Three experienced thoracic radiologists identified true locations of nodules (n = 516, 3-20-mm diameters) with CT and recommended case management by using Fleischner Society guidelines. Five other radiologists marked nodules and indicated case management by using images from conventional chest radiography, conventional chest radiography plus DE imaging, tomosynthesis, and tomosynthesis plus DE imaging. Sensitivity, specificity, and overall accuracy were measured by using the free-response receiver operating characteristic method and the receiver operating characteristic method for nodule detection and case management, respectively. Results were further analyzed according to nodule diameter categories (3-4 mm, .4 mm to 6 mm, .6 mm to 8 mm, and .8 mm to 20 mm). Results:Maximum lesion localization fraction was higher for tomosynthesis than for conventional chest radiography in all nodule size categories (3.55-fold for all nodules, P , .001; 95% confidence interval [CI]: 2.96, 4.15). Case-level sensitivity was higher with tomosynthesis than with conventional chest radiography for all nodules (1.49-fold, P , .001; 95% CI: 1.25, 1.73). Case management decisions showed better overall accuracy with tomosynthesis than with conventional chest radiography, as given by the area under the receiver operating characteristic curve (1.23-fold, P , .001; 95% CI: 1.15, 1.32). There were no differences in any specificity measures. DE imaging did not significantly affect nodule detection when paired with either conventional chest radiography or tomosynthesis. Conclusion:Tomosynthesis outperformed conventional chest radiography for lung nodule detection and determination of case management; DE imaging did not show significant differences over conventional chest radiography or tomosynthesis alone. These findings indicate performance likely achievable with a range of reader expertise.Online supplemental material is available for this article. Imaging data were collected from subjects at four tertiary care sitesthree in the United States and one in Sweden. The study (ClinicalTrials.gov no. NCT00963651) was approved by the institutional review board of each institution, and informed consent was obtained from each subject prior to enrollment. The study was compliant with the Health Insurance Portability and Accountability Act. Subjects enrolled were referred for, or had recently undergone,...

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Conventional chest radiography vs dual-energy computed radiography in the detection and characterization of pulmonary nodules.

Cited by 84 publications

References 28 publications

Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)

Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN)

Clinical results of CsI-detector-based dual-exposure dual energy in chest radiography

Multi-Institutional Evaluation of Digital Tomosynthesis, Dual-Energy Radiography, and Conventional Chest Radiography for the Detection and Management of Pulmonary Nodules

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