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10 - Satisfaction of Search in Radiology

from Part II - Science of Image Perception

Published online by Cambridge University Press:  20 December 2018

Ehsan Samei
Affiliation:
Duke University Medical Center, Durham
Elizabeth A. Krupinski
Affiliation:
Emory University, Atlanta
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Print publication year: 2018

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References

Agresti, A. (1990). Categorical Data Analysis. New York: John Wiley, pp. 244–245, 249250.Google Scholar
Anbari, M.M., West, O.C. (1997). Cervical spine trauma radiography: sources of false-negative diagnoses. Emerg Radiol, 4, 218224.Google Scholar
Beam, C.A., Krupinski, E.A., Kundel, H.L., Sickles, E.A., Wagner, R.F. (2006). The place of medical image perception in 21st-century health care. J Am Coll Radiol, 3, 409412.Google Scholar
Berbaum, K.S., Franken, E.A., Jr. (2006). Commentary: does clinical history affect perception? Acad Radiol, 13, 402403.Google Scholar
Berbaum, K.S., Schartz, K.M. (2013). One parameter contaminated binormal model (CBM) for analysis of difficult-to-fit ROC data. Proc SPIE, 8673, 86730C.CrossRefGoogle Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1986). Tentative diagnoses facilitate the detection of diverse lesions in chest radiographs. Invest Radiol, 21, 532539.Google Scholar
Berbaum, K.S., El-Khoury, G.Y., Franken, E.A., Jr., et al. (1988a). Impact of clinical history on fracture detection with radiography. Radiology, 168, 507511.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., Barloon, T.J. (1988b). Influence of clinical history upon detection of nodules and other lesions. Invest Radiol, 23, 4855.Google Scholar
Berbaum, K.S., Dorfman, D.D., Franken, E.A., Jr. (1989a). Measuring observer performance by ROC analysis: indications and complications. Invest Radiol, 24, 228233.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., El-Khoury, G.Y. (1989b). Impact of clinical history on radiographic detection of fractures: a comparison of radiologists and orthopedists. Am J Roentgenol, 153, 12211224.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1990). Satisfaction of search in diagnostic radiology. Invest Radiol, 25, 133140.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1991). Time-course of satisfaction of search. Invest Radiol, 26, 640648.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Anderson, K.L., et al. (1993). The influence of clinical history on visual search with single and multiple abnormalities. Invest Radiol, 28, 191201.Google Scholar
Berbaum, K.S., El-Khoury, G.Y., Franken, E.A., Jr., et al. (1994a). Missed fractures resulting from satisfaction of search effect. Emerg Radiol, 1, 242249.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., Lueben, K.R. (1994b). Influence of clinical history on perception of abnormalities in pediatric radiographs. Acad Radiol, 1, 217223.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., et al. (1996). The cause of satisfaction of search effects in contrast studies of the abdomen. Acad Radiol, 3, 815826.Google Scholar
Berbaum, K.S., Franken, E.A. Jr., Dorfman, D.D., et al. (1998). Role of faulty visual search in the satisfaction of search effect in chest radiology. Acad Radiol, 5, 919.CrossRefGoogle Scholar
Berbaum, K.S., Dorfman, D.D., Franken, E.A., Jr., Caldwell, R.T. (2000a). Proper ROC analysis and joint ROC analysis of the satisfaction of search effect in chest radiography. Acad Radiol, 7, 945958.CrossRefGoogle Scholar
Berbaum, K.S., Franken, E.A. Jr., Dorfman, D.D., Caldwell, R.T., Krupinski, E.A. (2000b). Role of faulty decision making in the satisfaction of search effect in chest radiography. Acad Radiol, 7, 10981106.CrossRefGoogle ScholarPubMed
Berbaum, K.S., Brandser, E.A., Franken, E.A., Jr., et al. (2001). Gaze dwell times on acute trauma injuries missed because of satisfaction of search. Acad Radiol, 8, 304314.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Dorfman, D.D., Caldwell, R.T., Lu, C.H. (2005). Can order of report prevent satisfaction of search in abdominal contrast studies? Acad Radiol, 12, 7484.Google Scholar
Berbaum, K.S., Franken, E.A., Jr., Caldwell, R.T., Schartz, K.M. (2006). Can a checklist reduce SOS errors in chest radiography? Acad Radiol, 13, 296304.Google Scholar
Berbaum, K.S., El-Khoury, G.Y., Ohashi, K., et al. (2007a). Satisfaction of search in multi-trauma patients: severity of detected fractures. Acad Radiol, 14, 711722.Google Scholar
Berbaum, K.S., Caldwell, R.T., Schartz, K.M., Thompson, B.H., Franken, E.A., Jr. (2007b). Does computer-aided diagnosis for lung tumors change satisfaction of search in chest radiography? Acad Radiol, 14, 10691076.Google Scholar
Berbaum, K.S., Schartz, K.M., Caldwell, R.T., et al. (2012). Satisfaction of search for subtle skeletal fractures may not be induced by more serious skeletal injury. J Am Coll Radiol, 9, 344351.Google Scholar
Berbaum, K.S., Schartz, K.M., Caldwell, R.T., et al. (2013). Satisfaction of search from detection of pulmonary nodules in computed tomography of the chest. Acad Radiol, 20, 194201.Google Scholar
Berbaum, K.S., Krupinski, E.A., Schartz, K.M., et al. (2015). Satisfaction of search in chest radiography 2015. Acad Radiol, 22, 14571465.CrossRefGoogle ScholarPubMed
Berbaum, K.S., Krupinski, E.A., Schartz, K.M., et al. (2016). The influence of a vocalized checklist on detection of multiple abnormalities in chest radiography. Acad Radiol, 23, 413420.Google Scholar
Berlin, L. (1996). Malpractice issues in radiology: perceptual errors. Am J Roentgenol, 167, 587590.Google Scholar
BMDP2V release: 8.0. (1993). BMDP Statistical Software, Inc. Statistical Solutions, Cork, Ireland (www.statsol.ie).Google Scholar
Bruning, J.L., Kintz, B.L. (1987). Computational Handbook of Statistics, 3rd edn. Glenview, IL: Harper Collins, pp. 272275.Google Scholar
Chakraborty, D.P., Winter, L.H.L. (1990). Free-response methodology: alternative analysis and a new observer-performance experiment. Radiology, 174, 873881.Google Scholar
Christensen, E.E., Murry, R.C., Holland, K., et al. (1981). The effect of search time on perception. Radiology, 138, 361365.CrossRefGoogle ScholarPubMed
Craik, K.J.W. (1943). The Nature of Explanation. London: Cambridge University Press, p. 81.Google Scholar
Dixon, W.J. (1992). BMDP Statistical Software Manual, Vol 1. Berkeley, CA: University of California Press, pp. 155174; 201227; 521564.Google Scholar
Dorfman, D.D., Alf, E., Jr. (1969). Maximum likelihood estimation of parameters of signal detection theory and determination of confidence intervals – rating method data. J Math Psychol, 6, 487496.CrossRefGoogle Scholar
Dorfman, D.D., Berbaum, K.S. (1986). RSCORE-J: pooled rating method data: a computer program for analyzing pooled ROC curves. Behav Res Methods Instrument, 18, 452462.Google Scholar
Dorfman, D.D., Berbaum, K.S. (1995). Degeneracy and discrete ROC rating data. Acad Radiol, 2, 907915.Google Scholar
Dorfman, D.D., Berbaum, K.S. (2000a). A contaminated binormal model for ROC data. II. A formal model. Acad Radiol, 7, 427437.Google Scholar
Dorfman, D.D., Berbaum, K.S. (2000b). A contaminated binormal model for ROC data. III. Initial evaluation with detection ROC data. Acad Radiol, 7, 438447.Google Scholar
Dorfman, D.D., Berbaum, K.S., Metz, C.E. (1992). Receiver operating characteristic rating analysis: generalization to the population of readers and patients with the jackknife method. Invest Radiol, 27, 723731.Google Scholar
Dorfman, D.D., Berbaum, K.S., Metz, C.E., et al. (1997). Proper receiver operating characteristic analysis: the bigamma model. Acad Radiol, 4, 138149.Google Scholar
Ericcson, K.A., Simon, H.A. (1980). Verbal reports as data. Psychol Rev, 87, 215251.Google Scholar
Ericcson, K.A., Simon, H.A. (1984). Protocol Analysis: Verbal Reports as Data. Cambridge, MA: MIT Press.Google Scholar
Fidler, J.L., Fletcher, J.G., Johnson, C.D., et al. (2004). Understanding interpretive errors in radiologists learning computed tomography colonography. Acad Radiol, 11, 750756.Google Scholar
Franken, E.A., Jr., Berbaum, K.S., Lu, C.H., et al. (1994). Satisfaction of search in detection of plain film abnormalities in abdominal contrast examinations. Invest Radiol, 29, 403409.Google Scholar
Gale, A.G., Worthington, B.S. (1983). The utility of scanning strategies in radiology. In: Eye Movements and Psychological Functions: International Views. Hillsdale, NJ: Lawrence Erlbaum, pp. 169191.Google Scholar
Gale, A.G., Johnson, F., Worthington, B.S. (1979). Psychology and radiology. In: Research in Psychology and Medicine, Vol 1. London: Academic Press.Google Scholar
Green, D.M., Swets, J.A. (1962). Signal Detection Theory and Psychophysics. New York, NY: John Wiley, pp. 86116.Google Scholar
Halsted, M.J., Kumar, H., Paquin, J.J., et al. (2004). Diagnostic errors by radiology residents in interpreting pediatric radiographs in an emergency setting. Pediatr Radiol, 34, 331336.Google Scholar
Hillis, S.L., Berbaum, K.S., Metz, C.E. (2008). Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis. Acad Radiol, 15, 647661.CrossRefGoogle ScholarPubMed
Hochberg, J. (1970). Attention, organization and consciousness. In: Attention: Contemporary Theory and Analysis. New York, NY: Appleton-Century Crofts.Google Scholar
Johnson, N.L., Kotz, S. (1970). Continuous Univariate Distributions. 1: Distributions in Statistics. New York, NY: John Wiley, pp. 186187.Google Scholar
Kinard, R.E., Orrison, W.W., Brogdon, B.G. (1986). The value of a worksheet in reporting body-CT examinations. Am J Roentgenol, 147, 848849.CrossRefGoogle ScholarPubMed
Kirk, R.E. (1982). Experimental Design, 2nd edn. Belmont, CA: Wadsworth, pp. 75; 429455; 531548.Google Scholar
Krupinski, E.A., Berbaum, K.S., Schartz, K.M., Caldwell, R.T., Madsen, M.T. (2017a). The impact of fatigue on satisfaction of search in chest radiography. Acad Radiol, 24, 10581063.Google Scholar
Krupinski, E.A., Schartz, K.M., Van Tassell, M.S., Madsen, M.T., Caldwell, R.T., Berbaum, K.S. (2017b). Effect of fatigue on reading computed tomography examination of the multiply injured patient. J Med Imag, 4, 035504.Google Scholar
Kuhn, G.J. (2002). Diagnostic errors. Acad Emerg Med, 9, 740750.Google ScholarPubMed
Kundel, H.L. (2006). History of research in medical image perception. J Am Coll Radiol, 3, 402408.Google Scholar
Kundel, H.L., LaFollette, P.S. (1972). Visual search patterns and experience with radiological images. Radiology, 103, 523528.CrossRefGoogle ScholarPubMed
Kundel, H.L., Nodine, C.F., Carmody, D. (1978). Visual scanning, pattern recognition and decision making in pulmonary nodule detection. Invest Radiol, 13, 175181.Google Scholar
Kundel, H.L., Nodine, C.F., Thickman, D., Toto, L. (1987). Searching for lung nodules: a comparison of human performance with random and systematic scanning models. Invest Radiol, 22, 417422.Google Scholar
Lev, M.H., Rhea, J.T., Bramson, R.T. (1999). Avoidance of variability and error in radiology. Lancet, 354, 272.Google Scholar
MacMahon, H., Engelmann, R., Behlen, F.M., et al. (1999). Computer-aided diagnosis of pulmonary nodules: results of a large-scale observer test. Radiology, 213, 723726.Google Scholar
Madsen, M.T., Berbaum, K.S., Ellingson, A.N., Thompson, B.H., Mullan, B.F., Caldwell, R.T. (2006). A new software tool for removing, storing, and adding abnormalities to medical images for perception research studies. Acad Radiol, 13, 305312.Google Scholar
McNemar, Q. (1969). Psychological Statistics, 4th edn. New York, NY: Wiley, pp. 5458.Google Scholar
Metz, C.E. (1987). Current problems in ROC analysis. In: Proceedings of the Chest Imaging Conference 1987. Madison, WI: University of Wisconsin, pp. 315336.Google Scholar
Most, S.B., Scholl, B.J., Clifford, E.R., Simons, D.J. (2005). What you see is what you set: sustained inattentional blindness and the capture of awareness. Psychol Rev, 112, 217242.Google Scholar
Nakamura, K., Yoshida, H., Engelmann, R., et al. (2000). Computerized analysis of the likelihood of malignancy in solitary pulmonary nodules with use of artificial neural networks. Radiology, 214, 823830.Google Scholar
Neisser, U. (1976). Cognition and Reality. San Francisco, CA: W.H. Freeman.Google Scholar
Newell, A., Simon, H.A. (1972). Human Problem Solving. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
Nodine, C.F., Kundel, H.L. (1987). Using eye movements to study visual search and to improve tumor detection. RadioGraphics, 7, 12411250.Google Scholar
Nodine, C.F., Mello-Thoms, C., Weinstein, S.P., et al. (2001). Blinded review of retrospectively visible unreported breast cancers: an eye-position analysis. Radiology, 221, 122129.Google Scholar
Nuñez, D.B. Jr., Quencer, R.M. (1998). The role of helical CT in the assessment of cervical spine injuries. Am J Roentgenol, 171, 951957.Google Scholar
Pesce, L.L., Metz, C.E. (2007). Reliable and computationally efficient maximum-likelihood estimation of “proper” binormal ROC curves. Acad Radiol, 14, 814829.Google Scholar
Rasband, W.S. (1997–2006). ImageJ. Bethesda, MD: US National Institutes of Health.Google Scholar
Renfrew, R.L., Franken, E.A., Berbaum, K.S., Weigelt, F.H., AbuYousef, M.M. (1992). Error in radiology: classification and lessons in 182 cases presented at a problem case conference. Radiology, 183, 145150.Google Scholar
Rogers, LF. (1982). Radiology of Skeletal Trauma. New York, NY: Churchill-Livingstone, p. 1.Google Scholar
Rogers, L.F. (1984). Common oversights in the evaluation of the patient with multiple injuries. Skelet Radiol, 12, 103111.Google ScholarPubMed
Rogers, L.F., Hendrix, R.W. (1990). Evaluating the multiply injured patient radiologically. Orthop Clin North Am, 21, 437447.Google Scholar
Samei, E. (2006). Why medical image perception? J Am Coll Radiol, 3, 400401.Google Scholar
Samuel, S., Kundel, H.L., Nodine, C.F., Toto, L.C. (1995). Mechanism of satisfaction of search: eye position recordings in the reading of chest radiographs. Radiology, 94, 895902.Google Scholar
Samuelson, F. (2011). The single-parameter power law for modeling data from observer experiments in medical imaging. Medical Image Perception Conference XIV, Dublin, Ireland.Google Scholar
Schartz, K.M., Berbaum, K.S., Caldwell, R.T., Madsen, M.T. (2009). WorkstationJ as ImageJ plugin for medical image studies. Annual Meeting of the Society for Imaging Informatics in Medicine (SIIM) – 9th Annual SIIM Research and Development Symposium, Charlotte, NC, June 6, 2009. www.siimweb.org/assets/FCBE219A-C30B-4003-9892-FACA9230AB91.pdf.Google Scholar
Schartz, K.M., Berbaum, K.M., Madsen, M.T., et al. (2013). Multiple diagnostic task performance in CT examination of the chest. Br J Radiol, 86, 20110799, Erratum in: Br J Radiol, 86, 20139001.Google Scholar
Schartz, K.M., Madsen, M.T., Kim, J., et al. (2016). Trauma in CT: the role of severe injury on satisfaction of search revised. J Am Coll Radiol, 13, 973978.Google Scholar
Simon, H.A. (1971). Designing organizations for an information-rich world. In: Computers, Communications, and the Public Interest. Baltimore, MD: Johns Hopkins Press, pp. 3752.Google Scholar
Sistrom, C. (2006). Radiology checklists, satisfaction of search, and the talking template concept. Acad Radiol, 13, 922923.Google Scholar
Sistrom, C.L., Langlotz, C.P. (2005) A framework for improved radiology reporting. J Am Coll Radiol, 2, 6167.Google Scholar
Smith, M.J. (1967). Error and Variation in Diagnostic Radiology. Springfield, IL: Charles C. Thomas, p. 27.Google Scholar
Snedecor, G.W., Cochran, W.G. (1989). Statistical Methods, 8th edn. Ames, IA: Iowa State University Press, pp. 146147.Google Scholar
Swensson, R.G. (1988). The effects of clinical information on film interpretation: another perspective. Invest Radiol, 23, 5661.Google Scholar
Swensson, R.G. (1996). Unified measurement of observer performance in detecting and localizing target objects on images. Med Phys, 23, 17091725.Google Scholar
Swensson, R.G., Theodore, G.H. (1990). Search and nonsearch protocols for radiographic consultation. Radiology, 177, 851856.Google Scholar
Swensson, R.G., Hessel, S.J., Herman, P.G. (1977). Omissions in radiology: faulty search or stringent reporting criteria? Radiology, 123, 563567.Google Scholar
Swensson, R.G., Hessel, S.J., Herman, P.G. (1979). Detection performance and the nature of the radiologist’s search task. In Symposium on the Optimization of Chest Radiography (Bureau of Radiological Health). Washington, DC: US Government Printing Office.Google Scholar
Swensson, R.G., Hessel, S.J., Herman, P.G. (1982). Radiographic interpretation with and without search: visual search aids the recognition of chest pathology. Invest Radiol, 17, 145151.Google Scholar
Swensson, R.G., Hessel, S.J., Herman, P.G. (1985). The value of searching films without specific preconceptions. Invest Radiol, 20, 100114.Google Scholar
Swensson, R.G., King, J.L., Gur, D. (2001). A constrained formulation for the receiver operating characteristic (ROC) curve based on probability summation. Med Phys, 28, 15971609.Google Scholar
Swets, J.A., Pickett, R.M. (1982). Evaluation of Diagnostic Systems: Methods from Signal Detection Theory. New York, NY: Academic Press.Google Scholar
Tuddenham, W.J. (1962). Visual search, image organization, and reader error in roentgen diagnosis: studies of the psychophysiology of roentgen image perception. Radiology, 78, 694704.Google Scholar
Tuddenham, W.J. (1963). Problems of perception in chest roentgenology: facts and fallacies. Radiol Clin N Am, 1, 227–289.Google Scholar
von Helmholtz, H. (1867, 1963). Handbook of Physiological Optics. New York, NY: Dover.Google Scholar
Voytovich, A., Rippey, R., Suffredini, A. (1985). Premature conclusions in diagnostic reasoning. J Med Educ, 60, 302307.Google Scholar
Xu, X.W., Doi, K., Kobayashi, T., MacMahon, H., Giger, M.L. (1997). Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. Med Phys, 24, 13951403.Google Scholar

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