Fast and automatic bone segmentation and registration of 3D ultrasound to CT for the full pelvic anatomy: a comparative study

Ultrasound-based 3D bone modelling in computer assisted orthopedic surgery - a review and future challenges

Computer-assisted orthopedic surgery requires precise representations of bone surfaces. To date, computed tomography constitutes the gold standard, but comes with a number of limitations, including costs, radiation and availability. Ultrasound has potential to become an alternative to computed tomography, yet suffers from low image quality and limited field-of-view. These shortcomings may be addressed by a fully automatic segmentation and model-based completion of 3D bone surfaces from ultrasound images. This survey summarizes the state-of-the-art in this field by introducing employed algorithms, and determining challenges and trends. For segmentation, a clear trend toward machine learning-based algorithms can be observed. For 3D bone model completion however, none of the published methods involve machine learning. Furthermore, data sets and metrics are identified as weak spots in current research, preventing development and evaluation of models that generalize well.

Comparative use of ultrasound and radiography for the detection of fractures: a systematic review and narrative synthesis

Background

Traditionally, X-rays have remained the standard modality for bone fracture diagnosis. However, other diagnostic modalities most notably ultrasound have emerged as a simple, radiation-safe, effective imaging tool to diagnose bone fractures. Despite the advantages, there is a prevalent scarcity of literature recognizing its significance in bone trauma management. This review investigates the effectiveness of ultrasound in the diagnosis of various bone fractures when compared to conventional radiography such as X-rays.

Methodology

Electronic databases such as PubMed/Medline, SCOPUS, and Web of Science (WOS) were reviewed for observational studies and review articles from the years 2017-2022 utilizing MESH terminology in a broad term search strategy. The search returned a total of 248 articles. After removal of duplicates, abstract, and full-text screening this systematic review ultimately utilized data from 31 articles. All searches were performed and analyzed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology and were conducted during August 2022. In accordance with the guidelines for assessing the quality of included systematic reviews, we used the AMSTAR 2020, Supplemental Digital Content 2, http://links.lww.com/MS9/A241 (A Measurement Tool to Assess Systematic Reviews) tool to evaluate the methodological quality of the included studies. A data extraction form based on the Cochrane Consumers and Communication Review group's extraction template for quality assessment and evidence synthesis was used for data extraction. The information extracted included details such as author information, database, journal details, type of study, etc. Studies included will be classified into long bones, short bones, pneumatic bones, irregular bones, ankle and knee, stress fractures, hip fractures, POCUS, and others. All included studies considered bias and ethical criteria and provided valuable evidence to answer the research question.

Results

The search returned a total of 248 articles, with 192 articles remaining after the removal of duplicates. Primary screening of the title and abstract articles from the database search and additional sources identified 68 relevant articles for full-text screening. This systematic review ultimately used data from 33 articles of the remaining articles we included all of them because they had more than 70% certainty, using the STROBE tool for observational articles, narrative reviews with the ENTREQ guide, and systematic reviews and meta-analyses with the PRISMA guide; however, two articles were excluded at the eligibility stage because of risk of bias.

Conclusion

This systematic review provides insightful evidence on safety and effectiveness of ultrasound in diagnosing fractures when compared to the conventional imaging modalities such as X-rays. This shall promote further large-scale, multi-centre research that can eventually guide clinic practice in diagnosing and managing various bone fractures.

Feasibility of tracked ultrasound registration for pelvic-abdominal tumor navigation: a patient study

PURPOSE

Surgical navigation techniques can guide surgeons in localizing pelvic-abdominal malignancies. For abdominal navigation, accurate patient registration is crucial and is generally performed using an intra-operative cone-beam CT (CBCT). However, this method causes 15-min surgical preparation workflow interruption and radiation exposure, and more importantly, it cannot be repeated during surgery to compensate for large patient movement. As an alternative, the accuracy and feasibility of tracked ultrasound (US) registration are assessed in this patient study.

METHODS

Patients scheduled for surgical navigation during laparotomy of pelvic-abdominal malignancies were prospectively included. In the operating room, two percutaneous tracked US scans of the pelvic bone were acquired: one in supine and one in Trendelenburg patient position. Postoperatively, the bone surface was semiautomatically segmented from US images and registered to the bone surface on the preoperative CT scan. The US registration accuracy was computed using the CBCT registration as a reference and acquisition times were compared. Additionally, both US measurements were compared to quantify the registration error caused by patient movement into Trendelenburg.

RESULTS

In total, 18 patients were included and analyzed. US registration resulted in a mean surface registration error of 1.2 ± 0.2 mm and a mean target registration error of 3.3 ± 1.4 mm. US acquisitions were 4 × faster than the CBCT scans (two-sample t-test P < 0.05) and could even be performed during standard patient preparation before skin incision. Patient repositioning in Trendelenburg caused a mean target registration error of 7.7 ± 3.3 mm, mainly in cranial direction.

CONCLUSION

US registration based on the pelvic bone is accurate, fast and feasible for surgical navigation. Further optimization of the bone segmentation algorithm will allow for real-time registration in the clinical workflow. In the end, this would allow intra-operative US registration to correct for large patient movement.

TRIAL REGISTRATION

This study is registered in ClinicalTrials.gov (NCT05637359).

Augmented Reality (AR) for Surgical Robotic and Autonomous Systems: State of the Art, Challenges, and Solutions

Despite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future.

Femur reconstruction in 3D ultrasound for orthopedic surgery planning

PURPOSE

Derotation varisation osteotomy of the proximal femur in pediatric patients usually relies on 2-dimensional X-ray imaging, as CT and MRI still are disadvantageous when applied in small children either due to a high radiation exposure or the need of anesthesia. This work presents a radiation-free non-invasive tool to 3D-reconstruct the femur surface and measure relevant angles for orthopedic diagnosis and surgery planning from 3D ultrasound scans instead.

METHODS

Multiple tracked ultrasound recordings are segmented, registered and reconstructed to a 3D femur model allowing for manual measurements of caput-collum-diaphyseal (CCD) and femoral anteversion (FA) angles. Novel contributions include the design of a dedicated phantom model to mimic the application ex vivo, an iterative registration scheme to overcome movements of a relative tracker only attached to the skin, and a technique to obtain the angle measurements.

RESULTS

We obtained sub-millimetric surface reconstruction accuracy from 3D ultrasound on a custom 3D-printed phantom model. On a pre-clinical pediatric patient cohort, angular measurement errors were [Formula: see text] and eventually [Formula: see text] for CCD and FA angles, respectively, both within the clinically acceptable range. To obtain these results, multiple refinements of the acquisition protocol were necessary, ultimately reaching success rates of up to 67% for achieving sufficient surface coverage and femur reconstructions that allow for geometric measurements.

CONCLUSION

Given sufficient surface coverage of the femur, clinically acceptable characterization of femoral anatomy is feasible from non-invasive 3D ultrasound. The acquisition protocol requires leg repositioning, which can be overcome using the presented algorithm. In the future, improvements of the image processing pipeline and more extensive surface reconstruction error assessments could enable more personalized orthopedic surgery planning using cutting templates.

Accurate and robust registration method for computer-assisted high tibial osteotomy surgery

PURPOSE

Computer-assisted high tibial osteotomy (HTO) is a frequently used treatment technique for lower extremity orthopedics, and its small incision and low exposure area are major limitations in tibial registration. This work combines skin surface features and gives a suitable registration algorithm based on Iterative Closest Points (ICP) algorithm to improve registration results. Furthermore, the precision, stability and efficiency of the described method is evaluated.

METHODS

After the initialization stage, the bone surface and skin surface data are combined to construct registration features. Then, a steepest perturbation search method is performed after the ICP algorithm (SPS-ICP) to obtain the optimal transformation through several iterations. Finally, the registration result is evaluated by establishing ground-truth through manual landmarks.

RESULTS

Phantom experiments including simulated human tissue show that the proximal fiducial registration error (FRE) of our method can reach 0.80 ± 0.30 mm (mean ± SD) with an overall rotational error < 1° and translational error < 1.5 mm. Furthermore, it remains stable when the point set is sparse. The average registration time is less than 40 s to ensure the high efficiency of surgical operation.

CONCLUSIONS

The approach fully describes a well-defined framework without additional imaging acquisition equipment for Computer-assisted HTO. By the experiment on the basis of a phantom with simulated soft tissue, the proposed method enables the accurate and robust registration of the tibia, and its computation time meets the demands of surgery.

Imaging, post-processing and navigation: Surgical applications in pelvic fracture treatment

Technical advancements of the past decade have led to massive improvements regarding imaging and visualization in trauma care. Digital imaging technology has fundamentally changed most processes in fracture management. However, the digital revolution in trauma surgery has just begun. Optical tracking navigation is currently the gold standard for positioning of implants for advanced applications in trauma surgery. Digital technology may enable the surgeon to achieve the same level of safety even in non-navigated placement of screws: We developed a new planning tool to transcript a preoperative into a semi-transparent "fluoroscopic like" image that can be identified intraoperatively and used as a map for the safe placement of sacro-iliac screws based on the "vestibule concept". In the future, development of artificial intelligence algorithms may provide features like automated segmentation of bone-fragments and other applications for a systematic fracture analysis to improve the standard of care in trauma surgery. Digital transformation has massive impact on diagnostics and surgical management of pelvic fractures. Improved visualization technology provides a better understanding of the surgical anatomy of the pelvis and may enable the surgeon to achieve greatest safety in percutaneous placement of screws even without using optical tracking navigation tools. The "para-axial fusion technique" is a useful tool to plan fluoroscopic views based on a 3D dataset prior to the surgery.

Three-dimensional ultrasound for knee osteophyte depiction: a comparative study to computed tomography

Purpose

Osteophytes are common radiographic markers of osteoarthritis. However, they are not accurately depicted using conventional imaging, thus hampering surgical interventions that rely on pre-operative images. Studies have shown that ultrasound (US) is promising at detecting osteophytes and monitoring the progression of osteoarthritis. Furthermore, three-dimensional (3D) ultrasound reconstructions may offer a means to quantify osteophytes. The purpose of this study was to compare the accuracy of osteophyte depiction in the knee joint between 3D US and conventional computed tomography (CT).

Methods

Eleven human cadaveric knees were pre-screened for the presence of osteophytes. Three osteoarthritic knees were selected, and then, 3D US and CT images were obtained, segmented, and digitally reconstructed in 3D. After dissection, high-resolution structured light scanner (SLS) images of the joint surfaces were obtained. Surface matching and root mean square (RMS) error analyses of surface distances were performed to assess the accuracy of each modality in capturing osteophytes. The RMS errors were compared between 3D US, CT and SLS models.

Results

Average RMS error comparisons for 3D US versus SLS and CT versus SLS models were 0.87 mm ± 0.33 mm (average ± standard deviation) and 0.95 mm ± 0.32 mm, respectively. No statistical difference was found between 3D US and CT. Comparative observations of imaging modalities suggested that 3D US better depicted osteophytes with cartilage and fibrocartilage tissue characteristics compared to CT.

Conclusion

Using 3D US can improve the depiction of osteophytes with a cartilaginous portion compared to CT. It can also provide useful information about the presence and extent of osteophytes. Whilst algorithm improvements for automatic segmentation and registration of US are needed to provide a more robust investigation of osteophyte depiction accuracy, this investigation puts forward the potential application for 3D US in routine diagnostic evaluations and pre-operative planning of osteoarthritis.

Deformation of the Pelvic Arteries Caused by Pneumoperitoneum and Postural Changes in an Animal Model

BACKGROUND/AIM

We investigated pelvic arterial deformation and shift due to intraoperative pneumoperitoneum and postural changes in an animal model.

MATERIALS AND METHODS

Computed tomography images of pigs were acquired in different body positions (supine, head down at 5° and 10°, right lateral recumbent at 5° and 15°) before and after insufflation. We used a free software (3D Slicer) for image analysis. After landmark registration using 10 markers inserted into the pelvis, pelvic arterial deformation and shift of seven arterial bifurcation points were evaluated. The distance moved was the target registration error (TRE) from the points registered in the supine position. Fiducial registration error (FRE) was measured using the 10 pelvic markers.

RESULTS

TRE average from postural changes ranged from 0.7 to 1.2 mm and was 1.4 mm due to pneumoperitoneum. TRE and FRE averages were 2.1 mm and 0.2 mm, respectively.

CONCLUSION

The pelvis was useful for registering anatomical landmarks.

HFUS Imaging of the Cochlea: A Feasibility Study for Anatomical Identification by Registration with MicroCT

Cochlear implantation consists in electrically stimulating the auditory nerve by inserting an electrode array inside the cochlea, a bony structure of the inner ear. In the absence of any visual feedback, the insertion results in many cases of damages of the internal structures. This paper presents a feasibility study on intraoperative imaging and identification of cochlear structures with high-frequency ultrasound (HFUS). 6 ex-vivo guinea pig cochleae were subjected to both US and microcomputed tomography (µCT) we respectively referred as intraoperative and preoperative modalities. For each sample, registration based on simulating US from the scanner was performed to allow a precise matching between the visible structures. According to two otologists, the procedure led to a target registration error of 0.32 mm ± 0.05. Thanks to referring to a better preoperative anatomical representation, we were able to intraoperatively identify the modiolus, both scalae vestibuli and tympani and deduce the location of the basilar membrane, all of which is of great interest for cochlear implantation. Our main objective is to extend this procedure to the human case and thus provide a new tool for inner ear surgery.

Ultrasound Bone Segmentation: A Scoping Review of Techniques and Validation Practices

Ultrasound bone segmentation is an important yet challenging task for many clinical applications. Several works have emerged attempting to improve and automate bone segmentation, which has led to a variety of computational techniques, validation practices and applied clinical scenarios. We characterize this exciting and growing body of research by reviewing published ultrasound bone segmentation techniques. We review 56 articles in detail and categorize and discuss the image analysis techniques that have been used for bone segmentation. We highlight the general trends of this field in terms of clinical motivation, image analysis techniques, ultrasound modalities and the types of validation practices used to quantify segmentation performance. Finally, we present an outlook on promising areas of research based on the unaddressed needs for solving ultrasound bone segmentation.