Orthopedic surgery remains technically demanding due to the complex anatomical structures and cumbersome surgical procedures. The introduction of image-guided orthopedic surgery (IGOS) has significantly decreased the surgical risk and improved the operation results. This review focuses on the application of recent advances in artificial intelligence (AI), deep learning (DL), augmented reality (AR) and robotics in image-guided spine surgery, joint arthroplasty, fracture reduction and bone tumor resection. For the pre-operative stage, key technologies of AI and DL based medical image segmentation, 3D visualization and surgical planning procedures are systematically reviewed. For the intra-operative stage, the development of novel image registration, surgical tool calibration and real-time navigation are reviewed. Furthermore, the combination of the surgical navigation system with AR and robotic technology is also discussed. Finally, the current issues and prospects of the IGOS system are discussed, with the goal of establishing a reference and providing guidance for surgeons, engineers, and researchers involved in the research and development of this area.

BACKGROUND: Detecting and interpreting changes in the images of follow-up CT scans by the clinicians is often time-consuming and error-prone due to changes in patient position and non-rigid anatomy deformations. Thus, reconstructed repeat scan images are required, precluding reduced dose sparse-view repeat scanning. OBJECTIVE: A method to automatically detect changes in a region of interest of sparse-view repeat CT scans in the presence of non-rigid deformations of the patient’s anatomy without reconstructing the original images. METHODS: The proposed method uses the sparse sinogram data of two CT scans to distinguish between genuine changes in the repeat scan and differences due to non-rigid anatomic deformations. First, size and contrast level of the changed regions are estimated from the difference between the scans’ sinogram data. The estimated types of changes in the repeat scan help optimize the method’s parameter values. Two scans are then aligned using Radon space non-rigid registration. Rays which crossed changes in the ROI are detected and back-projected onto image space in a two-phase procedure. These rays form a likelihood map from which the binary changed region map is computed. RESULTS: Experimental studies on four pairs of clinical lung and liver CT scans with simulated changed regions yield a mean changed region recall rate > 86%and a mean precision rate > 83%when detecting large changes with low contrast, and high contrast changes, even when small. The new method outperforms image space methods using prior image constrained compressed sensing (PICCS) reconstruction, particularly for small, low contrast changes (recall = 15.8%, precision = 94.7%). CONCLUSION: Our method for automatic change detection in sparse-view repeat CT scans with non-rigid deformations may assist radiologists by highlighting the changed regions and may obviate the need for a high-quality repeat scan image when no changes are detected.

BACKGROUND: Repeat CT scanning is ubiquitous in many clinical situations, e.g. to follow disease progression, to evaluate treatment efficacy, and to monitor interventional CT procedures. However, it incurs in cumulative radiation to the patient which can be significantly reduced by using a region of interest (ROI) and the existing baseline scan. OBJECTIVE: To obtain a high-quality reconstruction of a ROI with a significantly reduced X-ray radiation dosage that accounts for deformations. METHODS: We present a new method for deformable registration and image reconstruction inside an ROI in repeat CT scans with a highly reduced X-ray radiation dose based on sparse scanning. Our method uses the existing baseline scan data, a user-defined ROI, and a new sparse repeat scan to compute a high-quality repeat scan ROI image with a significantly reduced radiation dose. Our method first performs rigid registration between the densely scanned baseline and the sparsely scanned repeat CT scans followed by deformable registration with a low-order parametric model, both in 3D Radon space and without reconstructing the repeat scan image. It then reconstructs the repeat scan ROI without computing the entire repeat scan image. RESULTS: Our experimental results on clinical lung and liver CT scans yield a mean × 14 computation speedup and a × 7.6-12.5 radiation dose reduction, with a minor image quality loss of 0.0157 in the NRMSE metric. CONCLUSION: Our method is considerably faster than existing methods, thereby enabling intraoperative online repeat scanning that it is accurate and accounts for position, deformation, and structure changes at a fraction of the radiation dose required by existing methods.

Purpose The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. Methods We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Results Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Conclusions Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

Stereotactic radiosurgery (SRS) is a common treatment for intracranial meningiomas. SRS is planned on a pre-therapy gadolinium-enhanced T1-weighted MRI scan (Gd-T1w MRI) in which the meningioma contours have been delineated. Post-SRS therapy serial Gd-T1w MRI scans are then acquired for longitudinal treatment evaluation. Accurate tumor volume change quantification is required for treatment efficacy evaluation and for treatment continuation.

BACKGROUND:As part of an effort to improve upon the Snellen chart, we provide a standardized version of the ETDRS chart utilizing five characters in each row. The choice of five characters contradicts the recommended ten characters per row determined by the NAS-NRC, a committee established to provide guidelines for testing visual acuity. We set out to quantify the influence of varying the number of characters per line on the ETDRS chart with respect to the accuracy and reproducibility of visual acuity measurement.METHODS:Eleven different ETDRS charts were created, each with a different number of characters appearing in each row. A computer simulation was programmed to run 10,000 virtual patients, each with a unique visual acuity, false-positive and false-negative error value.RESULTS:Accuracy and reproducibility were found to roughly correlate with the number of characters present in each row, such that charts with 1, 3, 5, 7, 9, and 11 characters per row provided accuracy of 0.164, 0.094, 0.078, 0.073, 0.071, and 0.070 logMAR, respectively. A non-linear relationship was observed, with little improvement found beyond seven characters per row. In addition, charts with an even number of characters per row provided higher accuracy than their greater-number odd counterparts. In certain instances, accuracy and reproducibility were not well correlated.CONCLUSIONS:Increasing the number of characters per row in the ETDRS chart provides a trade-off between accuracy and test duration. An optimized chart layout would take these findings into account, allowing for the use of different chart layouts for clinical versus research settings.

Optic pathway gliomas (OPG) represent 5% of pediatric brain tumors and compose a major therapeutic dilemma to the treating physicians. While chemotherapy is widely used for these tumors, our ability to predict radiological response is still lacking. In this study, we use volumetric imaging to examine in detail the long‐term effect of chemotherapy on the tumor as well as its various sub‐components.

We present a new method for the retrieval radiological cases from a database of clinical cases described by terms from the RadLex lexicon. The input is an database of cases and a query consisting of the patient volumetric scan, a user-defined region of interest in it, and a list of RadLex from the radiological report. The output is list of the most relevant cases from the database in decreasing order. Our method uses the RadLex terms and their hierarchical representation to define a similarity metric between terms based on their relative location in the hierarchy. For this purpose, we develop the Augmented RadLex Graph, a data structure that augments the RadLex hierarchy with links derived from the terms in the case reports, and a search algorithm that ranks case similarity based on the link distance between the terms in the graph. Our method was evaluated in the VISCERAL Retrieval Benchmark Challenge on 8 queries and a database of 1,813 cases. It ranked first in 6 out of the 8 cases tested.

PURPOSE:A new stereo vision system is presented to quantify brain shift and pulsatility in open-skull neurosurgeries. METHODS:The system is endowed with hardware and software synchronous image acquisition with timestamp embedding in the captured images, a brain surface oriented feature detection, and a tracking subroutine robust to occlusions and outliers. A validation experiment for the stereo vision system was conducted against a gold-standard optical tracking system, Optotrak CERTUS. A static and dynamic analysis of the stereo camera tracking error was performed tracking a customized object in different positions, orientations, linear, and angular speeds. RESULTS:The system is able to detect an immobile object position and orientation with a maximum error of 0.5 mm and 1.6° in all depth of field, and tracking a moving object until 3 mm/s with a median error of 0.5 mm. Three stereo video acquisitions were recorded from a patient, immediately after the craniotomy. The cortical pulsatile motion was captured and is represented in the time and frequency domain. The amplitude of motion of the cloud of features' center of mass was inferior to 0.8 mm. Three distinct peaks are identified in the fast Fourier transform analysis related to the sympathovagal balance, breathing, and blood pressure with 0.03-0.05, 0.2, and 1 Hz, respectively. CONCLUSIONS:The stereo vision system presented is a precise and robust system to measure brain shift and pulsatility with an accuracy superior to other reported systems.

To implement and evaluate the performance of a computerized statistical tool designed for robust and quantitative analysis of hemodynamic response imaging (HRI) ‐derived maps for the early identification of colorectal liver metastases (CRLM).

The reliability of patient-specific finite element (FE) modelling is dependent on the ability to provide repeatable analyses. Differences of inter-operator generated grids can produce variability in strain and stress readings at a desired location, which are magnified at the surface of the model as a result of the partial volume edge effects (PVEEs). In this study, a new approach is introduced based on an in-house developed algorithm which adjusts the location of the model's surface nodes to a consistent predefined threshold Hounsfield unit value. Three cadaveric human femora specimens were CT scanned, and surface models were created after a semi-automatic segmentation by three different experienced operators. A FE analysis was conducted for each model, with and without applying the surface-adjustment algorithm (a total of 18 models), implementing identical boundary conditions. Maximum principal strain and stress and spatial coordinates were probed at six equivalent surface nodes from the six generated models for each of the three specimens at locations commonly utilised for experimental strain guage measurement validation. A Wilcoxon signed-ranks test was conducted to determine inter-operator variability and the impact of the PVEE-adjustment algorithm. The average inter-operator difference in stress values was significantly reduced after applying the adjustment algorithm (before: 3.32 +/- 4.35MPa, after: 1.47 +/- 1.77MPa, p=0.025). Strain values were found to be less sensitive to inter-operative variability (p=0.286). In summary, the new approach as presented in this study may provide a means to improve the repeatability of subject-specific FE models of bone obtained from CT data.

Background: Coronal tibiofemoral (CTF) subluxation is a common finding in knee osteoarthritis (OA) which can be related to poor pain scores and tibial spine impingement. In this study we describe a new method for measuring CTF subluxation and present validation of the method using cadaveric knees.Methods: A prototype software code based on the ICP mathematical algorithm was developed to measure CTF subluxation; the code finds the rigid transformation that best aligns the articular surfaces, measures CTF subluxation and the angle between articular surfaces. For validation, three stripped fresh frozen cadaveric knee specimens were transfixed to a specially designed knee fixation device where tibiofemoral angle and CTF subluxation can be measured directly. Fluoroscopic images were obtained with the tibiofemoral joint in neutral alignment and with 5, 10 and 15 (mm) of medial and lateral subluxation. This procedure was repeated with a neutral tibiofemoral angle, 10 degrees of varus and 10 degrees of valgus. All images were analyzed independently by two investigators using the prototype software.Results: The interclass correlation coefficient between the two investigators for CTF subluxation and tibiofemoral angle was 0.93 and 0.99 respectively. The CTF subluxation and tibiofemoral angle measured by the software correlated to the CTF subluxation and tibiofemoral angle were defined using the knee fixation device, with Pearson product moments of 0.86 and 0.94 respectively.Conclusion: Our suggested prototype software is precise, repeatable and reliable at measuring CTF subluxation and tibiofemoral angle. It may prove to be a useful tool to evaluate CTF subluxation in a clinical setting. (C) 2014 Elsevier B.V. All rights reserved.

PURPOSETracking the progression of low grade tumors (LGTs) is a challenging task, due to their slow growth rate and associated complex internal tumor components, such as heterogeneous enhancement, hemorrhage, and cysts. In this paper, the authors show a semiautomatic method to reliably track the volume of LGTs and the evolution of their internal components in longitudinal MRI scans.METHODSThe authors' method utilizes a spatiotemporal evolution modeling of the tumor and its internal components. Tumor components gray level parameters are estimated from the follow-up scan itself, obviating temporal normalization of gray levels. The tumor delineation procedure effectively incorporates internal classification of the baseline scan in the time-series as prior data to segment and classify a series of follow-up scans. The authors applied their method to 40 MRI scans of ten patients, acquired at two different institutions. Two types of LGTs were included: Optic pathway gliomas and thalamic astrocytomas. For each scan, a "gold standard" was obtained manually by experienced radiologists. The method is evaluated versus the gold standard with three measures: gross total volume error, total surface distance, and reliability of tracking tumor components evolution.RESULTSCompared to the gold standard the authors' method exhibits a mean Dice similarity volumetric measure of 86.58% and a mean surface distance error of 0.25 mm. In terms of its reliability in tracking the evolution of the internal components, the method exhibits strong positive correlation with the gold standard.CONCLUSIONSThe authors' method provides accurate and repeatable delineation of the tumor and its internal components, which is essential for therapy assessment of LGTs. Reliable tracking of internal tumor components over time is novel and potentially will be useful to streamline and improve follow-up of brain tumors, with indolent growth and behavior.

Background: Accurate detection of the boundaries of the subthalamic nucleus (STN) in deep brain stimulation (DBS) surgery using microelectrode recording (MER) is considered to refine localization and may therefore improve clinical outcome. However, MER tends to extend operation time and its cost-utility balance has been debated. Objectives: To quantify the tradeoff between accuracy of STN localization and the spatial and temporal parameters of MER that effect the operation time using an automated detection method. Methods: We retrospectively estimated the accuracy of STN detection on data from 100 microelectrode trajectories. Our dense (average step = 0.12 mm) and long (average duration = 22.5 s) MER data was downsampled in the spatial and temporal domains. Then, the STN borders were detected automatically on both the downsampled and original data and compared to each other. Results: With a recording duration of 16 s, average accuracy for detecting STN entry ranged from 0.06 mm for a 0.1-mm step to 0.51 mm for a 1.0-mm step. Smaller effects were found along the temporal axis. For example, a 0.1-mm recording step yielded an STN entry average accuracy ranging from 0.06 mm for a 16-second recording duration to 0.16 mm for 0.1 s. Conclusions: STN entry detection error was about half of the step size. Sampling duration of STN activity can be minimized to 1 s/record without compromising accuracy. We conclude that bilateral DBS surgery time utilizing MER may be significantly shortened without compromising targeting accuracy.

Neuroimaging is a fundamental component of the neurological diagnosis. The greatly increased volume and complexity of neuroimaging datasets has created a need for efficient image management and retrieval. In this paper, we advance a content-based retrieval framework for 3D functional neuroimaging data based on 3D curvelet transforms. The localized volumetric texture feature was extracted by a 3D digital curvelet transform from parametric image of cerebral metabolic rate of glucose consumption with a set of adaptive disorder-oriented masks for each type of neurological disorder. The results, using 142 clinical dementia studies, show that our proposed approach supports efficient and high performance neuroimaging data retrieval.

This book presents the configuration space method for computer-aided design of mechanisms with changing part contacts. Configuration space is a complete and compact geometric representation of part motions and part interactions that supports the core mechanism design tasks of analysis, synthesis, and tolerancing. It is the first general algorithmic treatment of the kinematics of higher pairs with changing contacts. It will help designers detect and correct design flaws and unexpected kinematic behaviors, as demonstrated in the book's four case studies taken from industry. After presenting the configuration space framework and algorithms for mechanism kinematics, the authors describe algorithms for kinematic analysis, tolerancing, and synthesis based on configuration spaces. The case studies follow, illustrating the application of the configuration space method to the analysis and design of automotive, micro-mechanical, and optical mechanisms. Appendixes offer a catalog of higher-pair mechanisms and a description of HIPAIR, an open source C++ mechanical design system that implements some of the configuration space methods described in the book, including configuration space visualization and kinematic simulation. HIPAIR comes with an interactive graphical user interface and many sample mechanism input files. The Configuration Space Method for Kinematic Design of Mechanisms will be a valuable resource for students, researchers, and engineers in mechanical engineering, computer science, and robotics.

We present a new preoperative planning method for reducing the risk associated with insertion of straight tools in image-guided keyhole neurosurgery. The method quantifies the risks of multiple candidate trajectories and presents them on the outer head surface to assist the neurosurgeon in selecting the safest path. The surgeon can then define and/or revise the trajectory, add a new one using interactive 3D visualization, and obtain a quantitative risk measures. The trajectory risk is evaluated based on the tool placement uncertainty, on the proximity of critical brain structures, and on a predefined table of quantitative geometric risk measures. Our results on five targets show a significant reduction in trajectory risk and a shortening of the preoperative planning time as compared to the current routine method.

Intraoperative fluoroscopically based computed tomography, integrated with a navigation system, holds great potential for improving visualization and navigation in orthopedic procedures. However, a limited field of view generated by the fluoroscopically based computed tomography has imposed a serious limitation, especially for navigation-based procedures. The device presented in this article enables one to overcome the limitation of the small field of view. The device has been evaluated in vitro by five physicians and has been used successfully in one clinical case. In general, we have developed a simple, low-cost in-house device that helps overcome an intrinsic limitation of high-cost systems.