Computer-aided diagnosis: detection and characterization of hyperparathyroidism in digital hand radiographs

• Published in: Medical physics (Lancaster) Vol. 20; no. 4; p. 983
• Main Authors: Chang, C L, Chan, H P, Niklason, L T, Cobby, M, Crabbe, J, Adler, R S
• Format: Journal Article
• Language: English
• Published: United States 01.07.1993
• Subjects: Algorithms; Biophysical Phenomena; Biophysics; Evaluation Studies as Topic; Hand - diagnostic imaging; Humans; Hyperparathyroidism - diagnostic imaging; Models, Anatomic; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted
• DOI: 10.1118/1.596980
• ISSN: 0094-2405

An automated method is developed for the detection and staging of skeletal changes due to hyperparathyroidism on digitized hand radiographs. Subperiosteal bony resorption, particularly along the radial margins of the middle and proximal phalanges, is among the earliest manifestations of secondary hyperparathyroidism. In order to quantify the severity of bone resorption in these regions, the computer method analyzes the roughness of the phalangeal margins, as projected on the radiograph. The regions of interest, which contain the phalanges, are obtained from the digitized hand radiographs by an image preprocessor. The radial margin of each phalanx is detected by a model-guided boundary-tracking scheme. The roughness of these boundaries is then quantified by the mean-square variation and the first moment of the power spectrum. A receiver operating characteristic (ROC) study comparing the computer detection of hyperparathyroidism with the diagnosis by three experienced skeletal radiologists was performed by evaluating 84 hand images from 22 patients. Our present computer method can achieve a true-positive rate of 94% and a true-negative rate of 92%. Such a computer-aided diagnosis system may assist radiologists in their assessment of primary and secondary hyperparathyroidism, since it is both accurate and not subject to either intra- or interobserver variations.