انتشارات / RCBTR
تاریخ: 2020/06/01
توسط: Dr Alireza Ahmadian
منتشر شده در: international Journal of Medical Robotics and Computer Assisted Surgery
فایل های پیوست:
URL منتشر شده: https://pubmed.ncbi.nlm.nih.gov/31995264/

Samaneh Alimohamadi Gilakjan  Hossein Majedi  Bahador Makki Abadi  Alireza Ahmadian


Abstract


Background: Updating the statistical shape model (SSM) used in image guidance systems for the treatment of back pain using pre-op computed tomography (CT) and intra-op ultrasound (US) is challenging due to the scarce availability of pre-op images and the low resolution of the two imaging modalities.


Methods: A new approach is proposed here to update SSMs based on the sparse representation of the preoperative MRI images of patients as well as CT images, followed by displaying the injection needle and 3D tracking view of the patients' spine.


Results: The statistical analysis shows that updating the SSM using the patients' available MRI images (in more than 95% of the cases) instead of CT images (in less than 5%) will help maintain the required accuracy of needle injection based on the evaluation of injection in different parts of the phantom.


Conclusion: The results show that using the proposed model helps reduce the dosage and processing time significantly while maintaining the precision required for the pain procedures.


Keywords: back pain; image guidance systems; preoperative MRI images; statistical shape model.