title: An automatic segmentation method for regional analysis of femoral neck images acquired by pQCT.
abstract: We developed an automatic method for regional analysis of femoral neck images acquired by peripheral quantitative computed tomography (pQCT), based on automatic spatial re-alignment and segmentation; the segmentation method, based on a morphological approach, explicitly accounts for the presence of three different bone compartments: cortical region, trabecular region, and transition zone between cortical and trabecular compartments. The proposed method was applied on 13 femoral neck sections derived from female donors who were undergoing hip replacement surgery for primary degenerative arthritis or fracture, and a typical densitometric and structural analysis was performed both globally and regionally. The proposed segmentation method was quantitatively evaluated by comparing automatic contour and the corresponding manual contours delineated by three operators using metrics based on surface distance (average symmetric distance, ASD) and volumetric overlapping (dice similarity coefficient, DSC). The same approach was used to validate the automatic spatial orientation, considering as metric the difference between manual and automatic angle orientation. Results confirm a satisfactory agreement between automatic and manual performances (ASD < 0.41 mm, DSC > 0.91, orientation difference = 3.61°) and show that globally our algorithm performs very well. Concerning regional analysis application, from our results we can observe that significant differences are present among the four bone quadrants.
authors.affiliation: Institute of Molecular Bioimaging and Physiology (IBFM)-CNR, Palazzo LITA, via Fratelli Cervi 93, 20090, Segrate, Milan, Italy. giovanna.rizzo@ibfm.cnr.it
authors.forename: G
authors.initials: G
authors.lastname: Rizzo
authors.forename: E
authors.initials: E
authors.lastname: Scalco
authors.forename: D
authors.initials: D
authors.lastname: Tresoldi
authors.forename: I
authors.initials: I
authors.lastname: Villa
authors.forename: G L
authors.initials: GL
authors.lastname: Moro
authors.forename: C L
authors.initials: CL
authors.lastname: Lafortuna
authors.forename: A
authors.initials: A
authors.lastname: Rubinacci
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D005272:Femur Neck / Q000000981:diagnostic imaging*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity