Spatial resolution and chest nodule detection: an interesting incidental finding

This study reports an incidental finding from a larger work. It examines the relationship between spatial resolution and nodule detection for chest radiographs. Twelve examining radiologists with the American Board of Radiology read thirty chest radiographs in two conditions - full (1500 × 1500 pixel) resolution, and 300 × 300 pixel resolution linearly interpolated to 1500 × 1500 pixels. All images were surrounded by a 10-pixel sharp grey border to aid in focussing the observer's eye when viewing the comparatively unsharp interpolated images. Fifteen of the images contained a single simulated pulmonary nodule. Observers were asked to rate their confidence that a nodule was present on each radiograph on a scale of 1 (least confidence, certain no lesion is present) to 6 (most confidence, certain a lesion was present). All other abnormalities were to be ignored. No windowing, levelling or magnification of the images was permitted and viewing distance was constrained to approximately 70cm. Images were displayed on a 3 megapixel greyscale monitor. Receiver operating characteristic (ROC) analysis was applied to the results of the readings using the Dorfman-Berbaum-Metz multiplereader, multiple-case method. No statistically significant differences were found with either readers and cases treated as random or with cases treated as fixed. Low spatial frequency information appears to be sufficient for the detection of chest lesion of the type used in this study.

[1]  Stephen L Hillis,et al.  Power estimation for the Dorfman-Berbaum-Metz method. , 2004, Academic radiology.

[2]  C. Nodine,et al.  The Nature of Expertise in Radiology , 2000 .

[3]  Elizabeth A Krupinski,et al.  Evaluation of off-the-shelf displays for use in the American Board of Radiology maintenance of certification examination. , 2009, Radiology.

[4]  David J Manning,et al.  Ambient lighting: effect of illumination on soft-copy viewing of radiographs of the wrist. , 2007, AJR. American journal of roentgenology.

[5]  S. Hillis A comparison of denominator degrees of freedom methods for multiple observer ROC analysis , 2007, Statistics in medicine.

[6]  Ehsan Samei,et al.  Does image quality matter? Impact of resolution and noise on mammographic task performance. , 2007, Medical physics.

[7]  C Kimme-Smith,et al.  Effects of ambient light and view box luminance on the detection of calcifications in mammography. , 1997, AJR. American journal of roentgenology.

[8]  Alan Bishop,et al.  ROC Study of Four LCD Displays Under Typical Medical Center Lighting Conditions , 2005, Journal of Digital Imaging.

[9]  Stephen L Hillis,et al.  Monte Carlo validation of the Dorfman-Berbaum-Metz method using normalized pseudovalues and less data-based model simplification. , 2005, Academic radiology.

[10]  Mathias Prokop,et al.  Detectability of catheters on bedside chest radiographs: comparison between liquid crystal display and high-resolution cathode-ray tube monitors. , 2005, Radiology.

[11]  B. Wall,et al.  Radiation exposure of the UK population from medical and dental X-ray examinations. , 2001 .

[12]  K. Berbaum,et al.  Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method. , 1992, Investigative radiology.

[13]  K S Berbaum,et al.  Monte Carlo validation of a multireader method for receiver operating characteristic discrete rating data: factorial experimental design. , 1998, Academic radiology.

[14]  Peter Homolka,et al.  Impact of ambient light and window settings on the detectability of catheters on soft-copy display of chest radiographs at bedside. , 2003, AJR. American journal of roentgenology.

[15]  Stephen L Hillis,et al.  Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis. , 2008, Academic radiology.

[16]  C E Metz,et al.  Some practical issues of experimental design and data analysis in radiological ROC studies. , 1989, Investigative radiology.

[17]  B Julesz,et al.  Masking in Visual Recognition: Effects of Two-Dimensional Filtered Noise , 1973, Science.

[18]  Katherine P. Andriole,et al.  SCAR R&D Symposium 2003: Comparing the Efficacy of 5-MP CRT Versus 3-MP LCD in the Evaluation of Interstitial Lung Disease , 2004, Journal of Digital Imaging.

[19]  Mark McEntee,et al.  A software system for the simulation of chest lesions , 2007, SPIE Medical Imaging.

[20]  H E Rockette,et al.  Effects of luminance and resolution on observer performance with chest radiographs. , 2000, Radiology.

[21]  Mathias Prokop,et al.  Soft-Copy Reading of Digital Chest Radiographs: Effect of Ambient Light and Automatic Optimization of Monitor Luminance , 2005, Investigative radiology.

[22]  Michael D. Abràmoff,et al.  Image processing with ImageJ , 2004 .

[23]  Nancy A Obuchowski,et al.  A comparison of the Dorfman–Berbaum–Metz and Obuchowski–Rockette methods for receiver operating characteristic (ROC) data , 2005, Statistics in medicine.