Amaia Iribar-Zabala

Numerous minimally invasive procedures, including biopsies, ablations and neurostimulation, rely on the accurate placement of a needle under image guidance. Mixed reality (MR) head‐mounted displays (HMDs) offer a promising solution to enhance the guidance of these procedures without radiation. While the performance of the established HoloLens 2, now discontinued, is well‐documented, the clinical viability of its potential successors remains unproven. This study provides the first direct comparative benchmark of the HoloLens 2, Magic Leap 2 and Apple Vision Pro for a high‐precision needle insertion task, using sacral nerve stimulation (SNS) as a validation scenario. We developed custom applications for each platform and evaluated the performance with 11 users, including nine clinicians without prior HMD experience, through a randomized protocol. Quantitative and qualitative analyses were conducted to assess procedural efficiency and user experience. Results identified the Magic Leap 2 as the most effective platform, demonstrating significantly higher success rates and superior usability scores, driven by its ergonomic design and stable tracking. In contrast, the Apple Vision Pro, despite offering superior visual fidelity, proved unsuitable for this navigation task. Its performance was critically hampered by unstable marker tracking, significant device weight, and a lack of accommodation for prescription glasses, which disrupted the clinical workflow. The HoloLens 2 performed as a reliable, albeit less usable, baseline. We conclude that, for this surgical navigation purpose, the optimal HMD is determined by a balanced combination of tracking reliability, user comfort, and practical workflow integration, over the technical specifications of the device. These findings emphasize the importance of device selection in enhancing procedural outcomes and clinical training.

Objectives: Pelvic tumor resections demand high surgical precision to ensure clear margins while preserving function. Although patient-specific instruments (PSIs) improve osteotomy accuracy, positioning errors remain a limitation. This study evaluates the feasibility, accuracy, and usability of a novel dual-function augmented reality (AR) system for intraoperative guidance in PSI positioning and osteotomy execution using a head-mounted display (HMD). The system provides dual-function support by assisting both PSI placement and osteotomy execution. Methods: Ten fresh-frozen cadaveric hemipelves underwent AR-assisted internal hemipelvectomy, using customized 3D-printed PSIs and a new in-house AR software integrated into an HMD. Angular and translational deviations between planned and executed osteotomies were measured using postoperative CT analysis. Absolute angular errors were computed from plane normals; translational deviation was assessed as maximum error at the osteotomy corner point in both sagittal (pitch) and coronal (roll) planes. A Wilcoxon signed-rank test and Bland–Altman plots were used to assess intra-workflow cumulative error. Results: The mean absolute angular deviation was 5.11 ± 1.43°, with 86.66% of osteotomies within acceptable thresholds. Maximum pitch and roll deviations were 4.53 ± 1.32 mm and 2.79 ± 0.72 mm, respectively, with 93.33% and 100% of osteotomies meeting translational accuracy criteria. Wilcoxon analysis showed significantly lower angular error when comparing final executed planes to intermediate AR-displayed planes (p < 0.05), supporting improved PSI positioning accuracy with AR guidance. Surgeons rated the system highly (mean satisfaction ≥ 4.0) for usability and clinical utility. Conclusions: This cadaveric study confirms the feasibility and precision of an HMD-based AR system for PSI-guided pelvic osteotomies. The system demonstrated strong accuracy and high surgeon acceptance, highlighting its potential for clinical adoption in complex oncologic procedures.

Objectives: This pre-clinical feasibility study evaluates the accuracy of a novel augmented reality-based (AR-based) guidance technology using head-mounted displays (HMDs) for the placement of patient-specific instruments (PSIs)—also referred to as surgical guides—and osteotomy performance in pelvic tumour resections. The goal is to improve PSI placement accuracy and osteotomy execution while assessing user perception and workflow efficiency. Methods: The study was conducted on ten 3D-printed pelvic phantoms derived from CT scans of cadaveric specimens. Custom PSIs were designed and printed to guide osteotomies at the supraacetabular, symphysial, and ischial regions. An AR application was developed for the HoloLens 2 HMD to display PSI location and cutting planes. The workflow included manual supraacetabular PSI placement, AR-guided placement of the other PSIs and osteotomy execution. Postoperative CT scans were analysed to measure angular and distance errors in PSI placement and osteotomies. Task times and user feedback were also recorded. Results: The mean angular deviation for PSI placement was 2.20°, with a mean distance error of 1.19 mm (95% CI: 0.86 to 1.52 mm). Osteotomies showed an overall mean angular deviation of 3.73° compared to planned cuts, all within the predefined threshold of less than 5°. AR-assisted guidance added less than two minutes per procedure. User feedback highlighted the intuitive interface and high usability, especially for visualising cutting planes. Conclusions: Integrating AR through HMDs is a feasible and accurate method for enhancing PSI placement and osteotomy performance in pelvic tumour resections. The system provides reliable guidance even in cases of PSI failure and adds minimal time to the surgical workflow while significantly improving accuracy. Further validation in cadaveric models is needed to ensure its clinical applicability.

This study aims to develop a system based on mixed reality imaging for assistance in percutaneous ultrasound‐guided liver interventions. A liver phantom, an ultrasound scanner with an abdominal probe, an electromagnetic tracking system for localization of the ultrasound probe, and the percutaneous needle were used to develop the system. A gelatin liver phantom was fabricated, including a set of lesions (with agarose, glycerol, and sephadex) and artificial blood vessels 3D printed with thermoplastic polyurethane (TPU) elastic fibres. Intraoperative ultrasound images from a BK5000 ultrasound scanner were acquired using a video capture system and transmitted to 3D Slicer. The NDI Aurora electromagnetic tracking system, coupled to the ultrasound probe and intracorporeal needle, was used for real‐time trajectory tracking, providing us with spatial localization information. These images are then sent to the augmented reality HoloLens device as the primary visualization system. This work lays the groundwork for the development of a more comprehensive system to assist ultrasound‐guided percutaneous liver interventions in order to improve the accuracy and safety of these procedures. The use of mixed reality imaging technology allows a better integration of image‐guided surgery systems, such as the one presented in this work, in real clinical environments, and closer to the patient.

Patient‐specific implant placement in the case of pelvic tumour resection is usually a complex procedure, where the planned optimal position of the prosthesis may differ from the final location. This discrepancy arises from incorrect or differently executed bone resection and improper final positioning of the prosthesis. In order to overcome such mismatch, a navigation solution is presented based on an augmented reality application for HoloLens 2 to assist the entire procedure. This involves placing patient‐specific instruments for tumour resection guidance in the supraacetabular, ischial and symphysial regions, performing the osteotomy and assisting within the adequate positioning of the implant. The supraacetabular patient‐specific instrument and the prosthesis included optical markers attached to them to be used as reference for surgical guidance. The proposed application and workflow were validated by two clinicians on six phantoms, designed and fabricated from different cadaver specimens. The accuracy of the solution was evaluated by comparing the final position after navigation with the position defined in the surgical plan. Preliminary assessment shows promising results for the guidance system, with positive clinician feedback.

This work present a proof-of-concept of a robotic-driven intra-operative scanner designed for knee cartilage lesion repair, part of a system for direct in vivo bioprinting. The proposed system is based on a photogrammetric pipeline, which reconstructs the cartilage and lesion surfaces from sets of photographs acquired by a robotic-handled endoscope, and produces 3D grafts for further printing path planning. A validation on a synthetic phantom is presented, showing that —despite the cartilage smooth and featureless surface— the current prototype can accurately reconstruct osteochondral lesions and their surroundings with mean error values of 0.199 ± 0.096 mm but with noticeable concentration on areas with poor lighting or low photographic coverage. The system can also accurately generate grafts for bioprinting, although with a slight tendency to underestimate the actual lesion sizes, producing grafts with coverage errors of -12.2 ± 3.7, -7.9 ± 4.9 and -15.2 ± 3.4 % for the medio-lateral, antero-posterior and craneo-caudal directions respectively. Improvements in lighting and acquisition for enhancing reconstruction accuracy are planned as future work, as well as integration into a complete bioprinting pipeline and validation with ex vivo phantoms.

With the use of different technological equipment, it becomes a complex challenge to have a fully integrated operating room, with adequate communication between devices. In this paper, we present the Medical Image Guided and Holographic TherapY (MIGHTY) platform, a software development kit for surgical applications that integrates computer-assisted planning, augmented reality, real-time imaging and collaborative robotics in the same environment. To show MIGHTY’s capabilities, a representative use case – abdominal biopsy – is addressed. We tested quantitatively the throughput of the involved applications, and the precision of the scene-tracking methods. Throughput results scored satisfactorily high in regards to the system’s real-time performance, and the tracking methods, although improvable, were good for the purpose of this work, which aims on the integration and cooperation of all the involved technologies, rather than on the individual accuracy of each one of them.