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Bone ; 83: 9-16, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26456145

RESUMO

Methods currently used to analyse osteolytic lesions caused by malignancies such as multiple myeloma and metastatic breast cancer vary from basic 2-D X-ray analysis to 2-D images of micro-CT datasets analysed with non-specialised image software such as ImageJ. However, these methods have significant limitations. They do not capture 3-D data, they are time-consuming and they often suffer from inter-user variability. We therefore sought to develop a rapid and reproducible method to analyse 3-D osteolytic lesions in mice with cancer-induced bone disease. To this end, we have developed Osteolytica, an image analysis software method featuring an easy to use, step-by-step interface to measure lytic bone lesions. Osteolytica utilises novel graphics card acceleration (parallel computing) and 3-D rendering to provide rapid reconstruction and analysis of osteolytic lesions. To evaluate the use of Osteolytica we analysed tibial micro-CT datasets from murine models of cancer-induced bone disease and compared the results to those obtained using a standard ImageJ analysis method. Firstly, to assess inter-user variability we deployed four independent researchers to analyse tibial datasets from the U266-NSG murine model of myeloma. Using ImageJ, inter-user variability between the bones was substantial (±19.6%), in contrast to using Osteolytica, which demonstrated minimal variability (±0.5%). Secondly, tibial datasets from U266-bearing NSG mice or BALB/c mice injected with the metastatic breast cancer cell line 4T1 were compared to tibial datasets from aged and sex-matched non-tumour control mice. Analyses by both Osteolytica and ImageJ showed significant increases in bone lesion area in tumour-bearing mice compared to control mice. These results confirm that Osteolytica performs as well as the current 2-D ImageJ osteolytic lesion analysis method. However, Osteolytica is advantageous in that it analyses over the entirety of the bone volume (as opposed to selected 2-D images), it is a more rapid method and it has less user variability.


Assuntos
Processamento de Imagem Assistida por Computador , Neoplasias/complicações , Osteólise/diagnóstico por imagem , Osteólise/etiologia , Software , Animais , Automação , Neoplasias da Mama/complicações , Linhagem Celular Tumoral , Modelos Animais de Doenças , Feminino , Humanos , Masculino , Camundongos Endogâmicos BALB C , Pessoa de Meia-Idade , Neoplasias/patologia , Reprodutibilidade dos Testes , Interface Usuário-Computador , Microtomografia por Raio-X
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