Hadida Barzilai Dor, Tejman-Yarden Shai, Yogev David, Vazhgovsky Oliana, Nagar Netanel, Sasson Lior, Sion-Sarid Racheli, Parmet Yisrael, Goldfarb Abraham, Ilan Ophir
The Engineering Medical Research Lab, Sheba Medical Center, Ramat Gan, Israel.
The Edmond J. Safra International Congenital Heart Center, Sheba Medical Center, Ramat Gan, Israel.
Laryngoscope. 2025 Feb;135(2):894-900. doi: 10.1002/lary.31791. Epub 2024 Sep 24.
Mastoidectomy surgical training is challenging due to the complex nature of the anatomical structures involved. Traditional training methods based on direct patient care and cadaveric temporal bone training have practical shortcomings. 3D-printed temporal bone models and augmented reality (AR) have emerged as promising solutions, particularly for mastoidectomy surgery, which demands an understanding of intricate anatomical structures. Evidence is needed to explore the potential of AR technology in addressing these training challenges.
21 medical students in their clinical clerkship were recruited for this prospective, randomized controlled trial assessing mastoidectomy skills. The participants were randomly assigned to the AR group, which received real-time guidance during drilling on 3D-printed temporal bone models, or to the control group, which received traditional training methods. Skills were assessed on a modified Welling scale and evaluated independently by two senior otologists.
The AR group outperformed the control group, with a mean overall drilling score of 19.5 out of 25, compared with the control group's score of 12 (p < 0.01). The AR group was significantly better at defining mastoidectomy margins (p < 0.01), exposing the antrum, preserving the lateral semicircular canal (p < 0.05), sharpening the sinodural angle (p < 0.01), exposing the tegmen and attic, preserving the ossicles (p < 0.01), and thinning and preserving the external auditory canal (p < 0.05).
AR simulation in mastoidectomy, even in a single session, improved the proficiency of novice surgeons compared with traditional methods.
NA Laryngoscope, 135:894-900, 2025.
由于涉及的解剖结构复杂,乳突切除术的外科培训具有挑战性。基于直接患者护理和尸体颞骨训练的传统培训方法存在实际缺点。3D打印颞骨模型和增强现实(AR)已成为有前景的解决方案,特别是对于需要了解复杂解剖结构的乳突切除术。需要证据来探索AR技术在应对这些培训挑战方面的潜力。
招募了21名处于临床实习阶段的医学生参加这项评估乳突切除技能的前瞻性随机对照试验。参与者被随机分配到AR组,该组在3D打印颞骨模型上钻孔时接受实时指导,或分配到对照组,该组接受传统培训方法。技能通过改良的韦林量表进行评估,并由两名资深耳科医生独立评估。
AR组的表现优于对照组,在25分的总分中,平均总体钻孔得分为19.5分,而对照组得分为12分(p < 0.01)。AR组在确定乳突切除边缘(p < 0.01)、暴露鼓窦、保留外侧半规管(p < 0.05)、锐化窦硬膜角(p < 0.01)、暴露颅中窝和上鼓室、保留听小骨(p < 0.01)以及变薄和保留外耳道(p < 0.05)方面明显更好。
与传统方法相比,即使在单次训练中,乳突切除术中的AR模拟也提高了新手外科医生的熟练程度。
无 喉镜,135:894 - 900,2025年。