The level of fit and fill of the prosthetic stem in the femoral canal is an important parameter when planning a cementless total hip arthroplasty. However, the standard templates used in combination with radiographs are not always effective in the pre-operative evaluation of the level of fitting. For this reason, two algorithms were developed able to provide clinically relevant three-dimensional indicators of the implant fit and fill in the host femur, based on the CT data of each specific patient as collected in vivo. In this study the computational methods were described and validated using digital phantom datasets. Then the algorithms were applied for in vivo datasets and the sensitivity of each indicator was evaluated. The validation showed that the two algorithms are accurate from a computational point of view. Moreover, the in vivo testing demonstrated that the developed methods provide reasonable quantitative indicators of the stem positioning in the femoral CT dataset. © 2003 Elsevier Ireland Ltd. All rights reserved.
Sironi, G., Boella, G., Gervasi, M., Tartari, A., Zannoni, M. (2003). Observations at millimetric and submillimetric wavelenghts from Antarctica: Activity Report. MEMORIE DELLA SOCIETÀ ASTRONOMICA ITALIANA, 74(1), 85-88.
Observations at millimetric and submillimetric wavelenghts from Antarctica: Activity Report
SIRONI, GIORGIO;BOELLA, GIULIANO FILIPPO;GERVASI, MASSIMO;ZANNONI, MARIO
2003
Abstract
The level of fit and fill of the prosthetic stem in the femoral canal is an important parameter when planning a cementless total hip arthroplasty. However, the standard templates used in combination with radiographs are not always effective in the pre-operative evaluation of the level of fitting. For this reason, two algorithms were developed able to provide clinically relevant three-dimensional indicators of the implant fit and fill in the host femur, based on the CT data of each specific patient as collected in vivo. In this study the computational methods were described and validated using digital phantom datasets. Then the algorithms were applied for in vivo datasets and the sensitivity of each indicator was evaluated. The validation showed that the two algorithms are accurate from a computational point of view. Moreover, the in vivo testing demonstrated that the developed methods provide reasonable quantitative indicators of the stem positioning in the femoral CT dataset. © 2003 Elsevier Ireland Ltd. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.