Pulmonary nodule detection for metastatic disease screening poses a challenge in human and veterinary medicine. Computed tomography has been proven superior to conventional radiography for the detection of pulmonary nodules in humans.1–4 Currently, a 3-view (left lateral, right lateral, and ventrodorsal or dorsoventral) radiographic evaluation of the thorax is considered the standard of care for evaluation of pulmonary metastasis and other lung lesions in veterinary patients.5,6 Studies6–11 in dogs and cats have estimated the sensitivity of radiographic detection of metastatic nodules to range from 64% to 97%. The staging of malignant disease is partially based on the extent of metastasis to distant tissues, and detection of pulmonary nodules can greatly influence treatment decisions for the clinician and pet owner.
The implementation of DR in veterinary medicine has provided the opportunity to greatly improve patient imaging efficiency and distribution of images for interpretation.12–15 Postprocessing algorithms for viewing digital radiographs allow the reviewer to manipulate an image to individual preferences.16 Any postprocessing that would help to improve interpretation efficiency and minimize the possibility of missed lesions would be beneficial.
The use of DR is well-established in humans, and human clinical trials have focused on the use of postprocessing manipulation for the detection of pulmonary nodules.17–25 One form of postprocessing that has been evaluated in humans is reversal of the image grayscale, which produces a positive or inverted image in which the background contrast is shifted so that areas that originally were dark (eg, aerated lung) become bright on the inverted image.17 Thus, bone appears black, and air spaces appear white. It has been postulated that nodules that are summated over a soft tissue opaque region (eg, cardiac silhouette, mediastinum, or diaphragm) in a standard (negative image) display are surrounded by a darker background when the display grayscale is inverted. If nodules are more apparent when superimposed against a darker background, this type of inverted display may aid in the detection of pulmonary nodules.17 This display mode was originally thought to provide an easier means of detecting structures that have low contrast in humans; however, in a study26 performed in 1983, this was described as a subjective finding and was not critically evaluated.
The benefit of specific methods of radiographic postprocessing has not been well documented in veterinary medicine; most information on this subject is anecdotal or extrapolated from studies in humans. The purpose of the study reported here was to determine intra- and interobserver variability of 2 board-certified veterinary radiologists and 2 veterinary general practitioners for pulmonary nodule detection in SDIs and IDIs of digital thoracic radiographs of dogs as a means of evaluating the utility of these methods. The null hypotheses were that no intraobserver variability would be determined for detection of pulmonary nodules between the 2 display modes, and that no interobserver variability would be detected between the 2 radiologists and 2 veterinary general practitioners for pulmonary nodule detection in radiographs viewed in SDI or IDI modes.
Inverted display image
Receiver operating characteristic
Standard display image
Kodak CR 850 System, Carestream Health, Rochester, NY.
Sound-Eklin EDR6, Sound-Eklin Medical Systems Inc, Carlsbad, Calif.
eFilm Workstation 2.1, version 2.1.2, Merge Healthcare, Milwaukee, Wis.
WIDE IF2103M LCD 3M pixel, Wide Co Ltd, Cheongwon-gun, Chungbuk, Korea.
Kodak DX Workstation System 5, Carestream Health, Health Imaging Group, Rochester, NY.
Analyse-it, version 2.12, Analyse-it Software Ltd, Leeds, West Yorkshire, England.
PASS 2008, NCSS, Kaysville, Utah.
Dinkel E, Mundinger A, Schopp D, et al. Diagnostic imaging in metastatic lung disease. Lung 1990; 168(suppl): 1129–1136.
Davis SD. CT evaluation for pulmonary metastases in patients with extrathoracic malignancy. Radiology 1991; 180: 1–12.
Muhm JR, Brown LR, Crowe JK. Use of computed tomography in the detection of pulmonary nodules. Mayo Clin Proc 1977; 52: 345–348.
Muhm JR, Brown LR, Crowe JK. Detection of pulmonary nodules by computed tomography. AJR Am J Roentgenol 1977; 128: 267–270.
Forrest LJ. Radiology corner—advantages of the three view thoracic radiographic examination in instances other than metastasis. Vet Radiol Ultrasound 1992; 33: 340–341.
Lang J, Wortman JA, Glickman LT, et al. Sensitivity of radiographic detection of lung metastases in the dog. Vet Radiol 1986; 27: 74–78.
Suter PF, Carrig CB, O'Brien TR, et al. Radiographic recognition of primary and metastatic pulmonary neoplasms of dogs and cats. Vet Radiol Ultrasound 1974; 15: 3–24.
Tiemessen I. Thoracic metastases of canine mammary gland tumors. A radiographic study. Vet Radiol 1989; 30: 249–252.
Holt D, Van Winkle T, Schelling C, et al. Correlation between thoracic radiographs and postmortem findings in dogs with hemangiosarcoma: 77 cases (1984–1989). J Am Vet Med Assoc 1992; 200: 1535–1539.
Hammer AS, Bailey MQ, Sagartz JE. Retrospective assessment of thoracic radiographic findings in metastatic canine hemangiosarcoma. Vet Radiol Ultrasound 1993; 34: 235–238.
Barthez PY, Hornof WJ, Théon AP, et al. Receiver operating characteristic curve analysis of the performance of various radiographic protocols when screening dogs for pulmonary metastases. J Am Vet Med Assoc 1994; 204: 237–240.
Kheddache S, Mansson LG, Angelhed JE, et al. Digital chest radiography: should images be presented in negative or positive mode? Eur J Radiol 1991; 13: 151–155.
Sheline ME, Brikman I, Epstein DM, et al. The diagnosis of pulmonary nodules: comparison between standard and inverse digitized images and conventional chest radiographs. AJR Am J Roentgenol 1989; 152: 261–263.
Manninen H, Partanen K, Lehtovirta J, et al. Image processing in digital chest radiography: effect on diagnostic efficacy. Eur J Radiol 1992; 14: 164–168.
Oestmann JW, Kushner DC, Bourgouin PM, et al. Subtle lung cancers: impact of edge enhancement and gray scale reversal on detection with digitized chest radiographs. Radiology 1988; 167: 657–658.
Oestmann JW, Rubens JR, Bourgouin PM, et al. Impact of postprocessing on the detection of simulated pulmonary nodules with digital radiography. Invest Radiol 1989; 24: 467–471.
MacMahon H, Metz CE, Doi K, et al. Digital chest radiography: effect on diagnostic accuracy of hard copy, conventional video, and reversed gray scale video display formats. Radiology 1988; 168: 669–673.
Ishida M, Doi K, Loo LN, et al. Digital image processing: effect on detectability of simulated low-contrast radiographic patterns. Radiology 1984; 150: 569–575.
Krupinski EA, Evanoff M, Ovitt T, et al. Influence of image processing on chest radiograph interpretation and decision changes. Acad Radiol 1998; 5: 79–85.
Ishigaki T, Endo T, Ikeda M, et al. Subtle pulmonary disease: detection with computed radiography versus conventional chest radiography. Radiology 1996; 201: 51–60.
Fraser RG, Breatnach E, Barnes GT. Digital radiography of the chest: clinical experience with a prototype unit. Radiology 1983; 148: 1–5.
Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148: 839–843.
Hanley JA, McNeil BJ. The meaning and use of the areas under a receiver operating characteristic (ROC) curve. Radiology 1982; 143: 29–36.
Armbrust LJ, Hoskinson JJ, Biller DS, et al. Comparison of digitized and direct viewed (analog) radiographic images for detection of pulmonary nodules. Vet Radiol Ultrasound 2005; 46: 361–367.