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DOI 10.1111/joa.13465

Медицинская библиотека · Journal of anatomy · 2021

Thickness accuracy of virtually designed patient-specific implants for large neurocranial defects.

Wittner Claudia, Borowski Markus, Pirl Lukas, Kastner Johann, Schrempf Andreas, Schäfer Ute, Trieb Klemens, Senck Sascha

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

The combination of computer-aided design (CAD) techniques based on computed tomography (CT) data to generate patient-specific implants is in use for decades. However, persisting disadvantages are complicated design procedures and rigid reconstruction protocols, for example, for tailored implants mimicking the patient-specific thickness distribution of missing cranial bone. In this study we used two different approaches, CAD- versus thin-plate spline (TPS)-based implants, to reconstruct extensive unilateral and bilateral cranial defects in three clinical cases. We used CT data of three complete human crania that were virtually damaged according to the missing regions in the clinical cases. In total, we carried out 132 virtual reconstructions and quantified accuracy from the original to the generated implant and deviations in the resulting implant thickness as root-mean-square error (RMSE). Reconstructions using TPS showed an RMSE of 0.08-0.18 mm in relation to geometric accuracy. CAD-based implants showed an RMSE of 0.50-1.25 mm. RMSE in relation to implant thickness was between 0.63 and 0.70 mm (TPS) while values for CAD-based implants were significantly higher (0.63-1.67 mm). While both approaches provide implants showing a high accuracy, the TPS-based approach additionally provides implants that accurately reproduce the patient-specific thickness distribution of the affected cranial region.

Для цитирования: Wittner Claudia, Borowski Markus, Pirl Lukas, Kastner Johann, Schrempf Andreas, Schäfer Ute, Trieb Klemens, Senck Sascha. Thickness accuracy of virtually designed patient-specific implants for large neurocranial defects.. Journal of anatomy. 2021. DOI: 10.1111/joa.13465.

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