[R01] Next-generation image-guided endoscopic sinus surgery using novel computer vision techniques

Ente: National Institute of Biomedical Imaging and Bioengineering

Scadenza: 2030-02-28

Importo max: 413.944 EUR

Paese: US

Descrizione

Chronic rhinosinusitis (CRS) is a persistent inflammatory disease affecting 1 in 8 adults in the US. CRS profoundly affects health-related quality-of-life and is commonly treated with endoscopic sinus surgery (ESS). ESS fails to induce durable symptom improvements in 25% of CRS patients and subsequent revision ESS is needed in 15-46% of cases due to persistent or recurrent symptoms after incomplete surgical dissection. Revision ESS has significantly lower success rates than primary ESS and independently predicts poorer clinical outcomes. Complete surgical dissection, ideally during the first ESS, is less costly and is most likely to improve symptoms. Therefore, tools that enable complete ESS are critical. Image-guided surgery (IGS) can facilitate surgical dissection in ESS by mapping the location of surgical instruments to preoperative computed tomography (CT) images. However, IGS systems have significant limitations: 1) high costs, driving lower IGS usage, especially in underserved groups; 2) loss of tracking accuracy during ESS; and 3) disparity between the static CT images and reality as ESS progresses. We aim to establish a computer vision-based navigation system that will: 1) greatly reduce the cost of surgical navigation by eliminating expensive IGS hardware, thereby democratizing the use of navigation; 2) achieve consistent submillimeter accuracy during ESS; and 3) enhance surgical completeness to drive better clinical outcomes in CRS patients. The objective of this proposal is to develop a low-cost vision-based navigation system that reflects dynamic changes in surgical anatomy on the CT, maps critical anatomy from the CT onto a 3D reconstruction of the surgical field, and continuously tracks surgical instruments that are in view, aggregating these data in real-time for visualization. The central hypothesis is that vision-based navigation will maintain accuracy during ESS and will display critical anatomic structures and up- to-date anatomic changes to the surgeon, yielding more precise and complete operations. The rationale is that vision-based navigation will significantly improve and democratize navigation facilitating superior clinical outcomes at a lower cost for a larger cross-section of the population. We will test the central hypothesis in 3 specific aims: 1) Optimize the accuracy of high-fidelity 3D reconstructions of the sinonasal cavity using custom Neural Radiance Field-based techniques during surgery; 2) Refine automated co-registration of the CT volumetric model and 3D surgical scene reconstruction to enable dynamic anatomic updates, anatomic landmark display, and continuous surgical instrument tracking; and 3) Optimize the clinical interface and speed of computer vision-based navigation to enhance surgical performance. We will apply innovative computer vision techniques that harness the expertise of our team of surgeons and engineers. This research is significant because vision- based navigation will reduce existing limitat Istituzione: UNIVERSITY OF WASHINGTON PI: Waleed M Abuzeid Progetto: 1R01EB039035-01

Settori: National Institute of Biomedical Imaging and Bioengineering

Vai al bando originale

Registrati gratis su Bandolo per trovare bandi compatibili con la tua azienda.