A quantification strategy for missing bone mass in case of osteolytic bone lesions. Issue 12 (11th November 2013)

• Record Type: Journal Article
• Authors: Fränzle, Andrea; Bretschi, Maren; Bäuerle, Tobias; Giske, Kristina; Hillengass, Jens; Bendl, Rolf
• Is Part Of: Medical physics. Volume 40:Issue 12(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-11-11
• Subjects: Computed tomography -- Reconstruction -- Registration -- Segmentation; bone -- computerised tomography -- image reconstruction -- image registration -- image segmentation -- mass measurement -- medical image processing -- physiological models -- statistical analysis; bone metastasis -- osteolytic lesions -- segmentation -- image analysis -- preclinical animal model; Computerised tomographs -- Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Medical imaging -- Cancer -- Computed tomography -- Biomedical modeling -- Medical image segmentation -- Decision trees -- Computer software -- Computer modeling -- Acceleration measurement -- Mass measurement; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4828843
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : Most of the patients who died of breast cancer have developed bone metastases. To understand the pathogenesis of bone metastases and to analyze treatment response of different bone remodeling therapies, preclinical animal models are examined. In breast cancer, bone metastases are often bone destructive. To assess treatment response of bone remodeling therapies, the volumes of these lesions have to be determined during the therapy process. The manual delineation of missing structures, especially if large parts are missing, is very time‐consuming and not reproducible. Reproducibility is highly important to have comparable results during the therapy process. Therefore, a computerized approach is needed. Also for the preclinical research, a reproducible measurement of the lesions is essential. Here, the authors present an automated segmentation method for the measurement of missing bone mass in a preclinical rat model with bone metastases in the hind leg bones based on 3D CT scans. Methods: : The affected bone structure is compared to a healthy model. Since in this preclinical rat trial the metastasis only occurs on the right hind legs, which is assured by using vessel clips, the authors use the left body side as a healthy model. The left femur is segmented with a statistical shape model which is initialised using the automatically segmented medullary cavity. The left tibia and fibula are segmented using volume growing starting at the tibia medullary cavity and stopping at the femur boundary. Masked images of both segmentations are mirrored along the median plane and transferred manually to the position of the affected bone by rigid registration. Affected bone and healthy model are compared based on their gray values. If the gray value of a voxel indicates bone mass in the healthy model and no bone in the affected bone, this voxel is considered to be osteolytic. Results: : The lesion segmentations complete the missing bone structures in a reasonable way. The mean ratio v r / v m of the reconstructed bone volume v r and the healthy model bone volume v m is 1.07, which indicates a good reconstruction of the modified bone. Conclusions: : The qualitative and quantitative comparison of manual and semi‐automated segmentation results have shown that comparing a modified bone structure with a healthy model can be used to identify and measure missing bone mass in a reproducible way.