Revolutionising orthopaedic imaging: From 2D radiography and computed tomography to 3D volumetric radiography

IF 2.7 Q2 ORTHOPEDICS Journal of Experimental Orthopaedics Pub Date : 2025-02-13 DOI:10.1002/jeo2.70161
Ben Efrima, Amit Benady, Jari Dahmen, Gino M. M. J. Kerkhoffs, Jon Karlsson, Federico Giuseppe Usuelli
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CBCT machines utilise X-rays in the form of a large cone that covers the designated surface to be examined. Unlike the traditional CT, CBCT machines employ rotating flat panel. This design allows the machine to irradiate a large volume area rather than a thin slice, requiring only a single rotation to gather all the necessary information for reconstructing the region of interest (ROI) and creating 3D reconstructions quickly, with low radiographic exposure. Moreover, the scanner is relatively small and affordable compared with spiral CT, making it suitable for in-office use. Finally, a major disadvantage of CBCT was its high susceptibility to metal artifacts. Currently, computer algorithms are implemented in the devices, as such, it is not any more of a problem than it is for conventional CT [<span>12</span>].</p><p>The concept of acquiring images in a vertical position, rather than solely horizontally, originated in dentistry with the clinical introduction of CBCT [<span>12</span>]. 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This development has made 3D image acquisition more accessible in the ordinary day-to-day practice.</p><p>While WBCT provides a reliable representation of the 3D morphology of the foot, standard imaging software still requires surgeons to rely on 2D slices in the coronal, axial, and sagittal planes within the 3D scan. Traditionally, creating accurate 3D models has required a manual segmentation process, where surgeons had to outline the 3D boundaries of each individual bone. The imaging analysis software would then analyse the manual segmentation to create a 3D model of the scanned area [<span>4-7</span>]. This segmentation process is time-consuming and has, therefore, been reserved only for selected cases and large referral centres.</p><p>In recent years, the rapid advancement of artificial intelligence (AI) technology has refined and improved this process. 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引用次数: 0

Abstract

Since its inception in 1972 [12], spiral computed tomography (CT) has become an invaluable diagnostic tool, offering precise three-dimensional (3D) image acquisition [3]. However, spiral CT has several potential limitations; it is relatively expensive and space-consuming, making it accessible only to large clinics or hospitals. Additionally, it requires high radiation exposure, posing potential risks to both patients and medical personnel. Lastly, image acquisition is performed in a non-weight-bearing position.

Cone beam computed tomography (CBCT) emerged in the late 1990s as an alternative. CBCT machines utilise X-rays in the form of a large cone that covers the designated surface to be examined. Unlike the traditional CT, CBCT machines employ rotating flat panel. This design allows the machine to irradiate a large volume area rather than a thin slice, requiring only a single rotation to gather all the necessary information for reconstructing the region of interest (ROI) and creating 3D reconstructions quickly, with low radiographic exposure. Moreover, the scanner is relatively small and affordable compared with spiral CT, making it suitable for in-office use. Finally, a major disadvantage of CBCT was its high susceptibility to metal artifacts. Currently, computer algorithms are implemented in the devices, as such, it is not any more of a problem than it is for conventional CT [12].

The concept of acquiring images in a vertical position, rather than solely horizontally, originated in dentistry with the clinical introduction of CBCT [12]. Over the last decade, vertical CBCT has been introduced to orthopaedic surgery in the form of weight-bearing CT (WBCT) [5-8, 13]. This technology enables image acquisition in the weight-bearing position, providing a 3D view of the upper and lower limb under the load of the body's weight. The use of WBCT has significantly improved the visualisation of foot and ankle morphology under load-bearing conditions, enhancing diagnostic capabilities and providing more precise postoperative follow-up. Consequently, in certain countries, surgeons are using WBCT as an in-office device, enabling orthopaedic surgeons to provide accurate 3D imaging already during patient visits without the need for referral to large medical centres. This development has made 3D image acquisition more accessible in the ordinary day-to-day practice.

While WBCT provides a reliable representation of the 3D morphology of the foot, standard imaging software still requires surgeons to rely on 2D slices in the coronal, axial, and sagittal planes within the 3D scan. Traditionally, creating accurate 3D models has required a manual segmentation process, where surgeons had to outline the 3D boundaries of each individual bone. The imaging analysis software would then analyse the manual segmentation to create a 3D model of the scanned area [4-7]. This segmentation process is time-consuming and has, therefore, been reserved only for selected cases and large referral centres.

In recent years, the rapid advancement of artificial intelligence (AI) technology has refined and improved this process. Currently, AI-powered imaging analysis software is capable of semi-automatic or fully automatic segmentation of accurate 3D models. This development effectively reduces the time-consuming segmentation process to a matter of minutes, making 3D imaging more widely available. This imaging analysis software includes several valuable complementary features, such as automatic angle measurement algorithms, distance mapping, and virtual osteotomy capabilities, enabling surgeons to plan osteotomies and complex procedures on 3D models and automatically calculate the post-surgical alignment of the foot and ankle [4-8]. The integration of WBCT and image analysis software renders the once complex, time-consuming, and expensive process of 3D image acquisition, segmentation, image analysis, and preoperative planning widely available to orthopaedic surgeons in general.

Achieving precise implementation of preoperative planning still requires advanced surgical capabilities. Currently, the most widely available tools for precision surgery available for orthopaedic surgeons are robot-assisted surgeries, CBCT-guided navigation, and patient-specific instruments [10, 14, 16]. All these methods have been validated and are currently in clinical use. They have been instrumental in improving precision, reducing surgical exposure, and enhancing patient-reported outcomes compared with standard surgical techniques. Patient-specific instrumentation has gained immense popularity over the past decade, largely due to advancements in 3D printing technology. This approach enables the custom manufacturing of surgical guides and implants, allowing for patient-specific surgical solutions [2]. In parallel, computer-guided navigation leverages three-dimensional images from cone-beam CT scans to guide and track surgical instruments or implants in real time, ensuring exceptional precision [9]. Robotic-assisted surgery allows for precise component placement and alignment using 3D precise bone cutting and soft-tissue alignment, based on preoperative planning [1]. Much like the original spiral CT, these surgical instruments are expensive and space-consuming, making them inaccessible to orthopaedic surgeons in general.

In recent years, there has been significant improvement in augmented reality (AR). This exponential improvement is directly correlated to the gradual infiltration of AI capabilities, which will reduce the computer power required for AR. AR goggles are becoming more affordable, and the idea of using AR for precision surgery has captured the imagination of many orthopaedic surgeons. However, to be acceptable for clinical use, AR must overcome three major obstacles: projection, registration, and navigation [11, 15].

In AR-guided surgery, the model is projected over the surgical site. An overly opaque projection can obscure the surgical site, while an overly transparent projection can make the surgical plan invisible. Therefore, one of the next challenges is to create a well-balanced projection that allows optimal visualisation of both the surgical site and the plan. The second challenge is registration or aligning the preoperative plan and projection with the actual surgical site. To accurately calibrate and locate the 3D projection, the AR software must be oriented to specific landmarks. Currently, a wide variety of registration tools are available, but they require rigorous validation processes in vitro before proceeding to clinical trials. The final obstacle is navigation, which involves performing the precision surgery. AR goggles can guide surgeons to the initial osteotomy, but once the morphology is altered, the preoperative plan may no longer be accurate. Accurate precision surgery needs to predict all surgical steps.

The rapid introduction of AI capabilities holds the potential to overcome all these obstacles. Accurate, reliable, and effective AR could, in theory, transform precision surgery in the same way that WBCT and AI-powered image analysis have revolutionised 3D imaging and analysis through decentralised access and diagnostic efficiency. AR could make precision surgery affordable and accessible to every surgeon.

The authors declare no conflict of interest.

None of the authors have financial or non-financial interests that are directly or indirectly related to the work submitted for publication except for. Federico G. Usuelli Reports: Relationship with Zimmer Biomet that includes: consulting or advisory and speaking and lecture fees. Relationship with Arthrex Inc that includes: consulting or advisory and speaking and lecture fees. Relationship with Episurf that includes: consulting or advisory and speaking and lecture fees. Relationship with Planmed Oy that includes: consulting or advisory and speaking and lecture fees. Relationship with Geistlich Pharma AG that includes: consulting or advisory and speaking and lecture fees. Relationship with BRM Trust that includes: consulting or advisory and speaking and lecture fees. Relationship with Paragon 28 Inc that includes: consulting or advisory, employment, paid expert testimony and speaking and lecture fees. Membership: International Editor Foot and Ankle International.

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革命性的骨科成像:从2D放射摄影和计算机断层摄影到3D体积放射摄影
自1972年诞生以来,螺旋计算机断层扫描(CT)已成为一种宝贵的诊断工具,提供精确的三维(3D)图像采集。然而,螺旋CT有几个潜在的局限性;它相对昂贵且占用空间,因此只有大型诊所或医院才能使用。此外,它需要高辐射暴露,对患者和医务人员都构成潜在风险。最后,在非承重位置进行图像采集。锥束计算机断层扫描(CBCT)在20世纪90年代末作为一种替代方案出现。CBCT机器利用x射线以大锥的形式覆盖指定的要检查的表面。与传统CT不同,CBCT采用旋转平板。这种设计允许机器照射大体积区域而不是薄片,只需要一次旋转就可以收集重建感兴趣区域(ROI)和快速创建3D重建所需的所有必要信息,并且放射照相曝光率低。此外,与螺旋CT相比,该扫描仪相对较小,价格实惠,适合在办公室使用。最后,CBCT的一个主要缺点是对金属伪影的高敏感性。目前,计算机算法在设备中实现,因此,与传统的CT[12]相比,它不再是一个问题。在垂直位置获取图像的概念,而不是仅仅在水平位置,起源于牙科临床引入CBCT[12]。在过去的十年中,立式CBCT以负重CT (WBCT)的形式被引入骨科手术[5- 8,13]。这项技术可以在负重位置进行图像采集,提供在身体重量负荷下的上肢和下肢的3D视图。WBCT的使用显著改善了负重条件下足部和踝关节形态的可视化,提高了诊断能力,并提供了更精确的术后随访。因此,在某些国家,外科医生正在使用WBCT作为办公室设备,使矫形外科医生能够在患者就诊期间提供准确的3D成像,而无需转诊到大型医疗中心。这一发展使得3D图像采集在日常实践中更加容易实现。虽然WBCT提供了足部三维形态的可靠表示,但标准成像软件仍然要求外科医生依赖3D扫描中冠状面、轴状面和矢状面的二维切片。传统上,创建精确的3D模型需要手动分割过程,外科医生必须勾勒出每个骨骼的3D边界。然后,成像分析软件对人工分割进行分析,生成扫描区域的三维模型[4-7]。这种分割过程耗时,因此只适用于选定的病例和大型转诊中心。近年来,人工智能(AI)技术的快速发展使这一过程得到了完善和改进。目前,人工智能成像分析软件能够半自动或全自动分割精确的3D模型。这一发展有效地将耗时的分割过程缩短到几分钟,使3D成像更广泛地应用。该成像分析软件包括几个有价值的互补功能,如自动角度测量算法、距离映射和虚拟截骨功能,使外科医生能够在3D模型上计划截骨和复杂的手术,并自动计算足和踝关节的术后对齐[4-8]。WBCT与图像分析软件的集成使得曾经复杂、耗时、昂贵的三维图像采集、分割、图像分析和术前规划的过程广泛应用于骨科医生。精确实施术前计划仍然需要先进的手术能力。目前,骨科医生最广泛使用的精确手术工具是机器人辅助手术、cbct引导导航和患者专用器械[10,14,16]。所有这些方法都经过了验证,目前正在临床应用。与标准手术技术相比,它们在提高精度、减少手术暴露和提高患者报告的结果方面发挥了重要作用。在过去的十年中,患者专用仪器获得了极大的普及,主要是由于3D打印技术的进步。这种方法可以定制外科导板和植入物的制造,允许患者特定的手术解决方案[2]。 与此同时,计算机导航利用锥束CT扫描的三维图像来实时引导和跟踪手术器械或植入物,确保了极高的精度。基于术前计划,机器人辅助手术允许使用3D精确骨切割和软组织对齐来精确放置和对齐部件。就像最初的螺旋CT一样,这些手术器械昂贵且占用空间,使得整形外科医生无法使用它们。近年来,增强现实(AR)技术有了显著的进步。这种指数级的进步与人工智能能力的逐渐渗透直接相关,这将降低AR所需的计算机功率。AR护目镜变得越来越便宜,使用AR进行精确手术的想法已经吸引了许多骨科医生的想象力。然而,要在临床应用中被接受,AR必须克服三个主要障碍:投影、注册和导航[11,15]。在ar引导的手术中,模型被投影到手术部位。过于不透明的投影会模糊手术部位,而过于透明的投影会使手术计划不可见。因此,接下来的挑战之一是创建一个平衡的投影,以实现手术部位和计划的最佳可视化。第二个挑战是术前计划和投影与实际手术部位的匹配或对齐。为了准确地校准和定位3D投影,AR软件必须面向特定的地标。目前,有各种各样的注册工具可用,但在进行临床试验之前,它们需要严格的体外验证过程。最后一个障碍是导航,这需要进行精确的手术。AR护目镜可以指导外科医生进行最初的截骨手术,但一旦形态学改变,术前计划可能不再准确。精确的外科手术需要预测所有的手术步骤。人工智能的快速引入有可能克服所有这些障碍。从理论上讲,准确、可靠和有效的增强现实技术可以改变精确手术,就像WBCT和人工智能图像分析通过分散访问和诊断效率彻底改变了3D成像和分析一样。增强现实技术可以让每个外科医生都能负担得起并获得精确的手术。作者声明无利益冲突。除以下情况外,所有作者均没有与提交出版的作品直接或间接相关的财务或非经济利益。Federico G. Usuelli报道:与Zimmer Biomet的关系包括:咨询或咨询以及演讲和讲座费用。与Arthrex Inc .的关系包括:咨询或咨询以及演讲和讲座费用。与Episurf的关系包括:咨询或咨询以及演讲和讲座费用。与planned Oy的关系包括:咨询或咨询以及演讲和讲座费用。与Geistlich Pharma AG的关系包括:咨询或咨询以及演讲和讲座费用。与BRM Trust的关系包括:咨询或咨询以及演讲和讲座费用。与Paragon 28 Inc .的关系,包括:咨询或咨询、雇佣、有偿专家证词以及演讲和讲座费用。会员资格:国际足踝部编辑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Experimental Orthopaedics
Journal of Experimental Orthopaedics Medicine-Orthopedics and Sports Medicine
CiteScore
3.20
自引率
5.60%
发文量
114
审稿时长
13 weeks
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