Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery.

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Integrating Upper-Limb Prostheses with the Human Body: Technology Advances, Readiness, and Roles in Human-Prosthesis Interaction.

Significant advances in bionic prosthetics have occurred in the past two decades. The field's rapid expansion has yielded many exciting technologies that can enhance the physical, functional, and cognitive integration of a prosthetic limb with a human. We review advances in the engineering of prosthetic devices and their interfaces with the human nervous system, as well as various surgical techniques for altering human neuromusculoskeletal systems for seamless human-prosthesis integration. We discuss significant advancements in research and clinical translation, focusing on upper limbprosthetics since they heavily rely on user intent for daily operation, although many discussed technologies have been extended to lower limb prostheses as well. In addition, our review emphasizes the roles of advanced prosthetics technologies in complex interactions with humans and the technology readiness levels (TRLs) of individual research advances. Finally, we discuss current gaps and controversies in the field and point out future research directions, guided by TRLs.

Prosthetic outcomes after amputation and the impact of mobility level on survival.

OBJECTIVE: Lower extremity amputation continues to be necessary in a significant number of patients with peripheral vascular disease. The 5-year survival following lower limb loss is markedly reduced. Many of these patients are never fitted with a prosthesis, and there is a dearth of knowledge regarding the barriers to prosthetic attainment. The goal of this study was to identify the risk factors for not receiving a prosthesis and the effect of mobility level on survival following major amputation. METHODS: This was a retrospective analysis of all patients that underwent lower extremity amputation by surgeons in our practice from January 1, 2010, to December 31, 2019. Abstracted data included: age, sex, race, body mass index, comorbidities, American Society of Anesthesiologists score, statin use, level of amputation, stump revision, fitting for prosthesis, type of prosthesis, and the United States' Medicare Functional Classification Level, also called K level. Survival was determined using a combination of sources, including the Social Security Death Master File, searches of multiple genealogic registries, and general internet searches. Multivariable logistic regression was used to determine risk factors associated with prosthesis attainment. Multivariable Cox proportional hazard regression with time-dependent covariates was performed to assess risk factors associated with 5-year mortality. RESULTS: A total of 464 patients were included in this study. The mean age was 65 years, and mean body mass index was 27 kg/m2. The majority of patients were male (68%), White (56%), diabetic (62%), and hypertensive (76%), and underwent below-the-knee amputation (69%). Prosthetic attainment occurred in 185 (40%). On multivariable analysis, age >81 years and current tobacco use were associated with no prosthetic fitting. Overall 5-year survival was 41.9% (95% confidence interval [CI], 37.6%-46.6%) (below-the-knee amputation, 47.7% [95% CI, 42.5%-53.5%]; above-the-knee amputation, 28.7% [95% CI, 22.1%-37.2%]). On multivariable analysis, age >60 years, congestive heart failure, above-the-knee amputation, and no prosthetic attainment were associated with decreased survival. Increasing K level was incrementally associated with improved survival. CONCLUSIONS: This study has identified several patient factors associated with prosthetic attainment, as well as multiple factors predictive of reduced survival after amputation. Being referred for prosthetic fitting was associated with improved survival not explained by patient characteristics and comorbidities. The Medicare Functional Classification Level K level predicts survival. More research is needed to determine the barriers to prosthetic attainment and if improving a patients K level will improve survival.

Neuromuscular implants: Interfacing with skeletal muscle for improved clinical translation of prosthetic limbs.

After an amputation, advanced prosthetic limbs can be used to interface with the nervous system and restore motor function. Despite numerous breakthroughs in the field, many of the recent research advancements have not been widely integrated into clinical practice. This review highlights recent innovations in neuromuscular implants-specifically those that interface with skeletal muscle-which could improve the clinical translation of prosthetic technologies. Skeletal muscle provides a physiologic gateway to harness and amplify signals from the nervous system. Recent surgical advancements in muscle reinnervation surgeries leverage the "bio-amplification" capabilities of muscle, enabling more intuitive control over a greater number of degrees of freedom in prosthetic limbs than previously achieved. We anticipate that state-of-the-art implantable neuromuscular interfaces that integrate well with skeletal muscle and novel surgical interventions will provide a long-term solution for controlling advanced prostheses. Flexible electrodes are expected to play a crucial role in reducing foreign body responses and improving the longevity of the interface. Additionally, innovations in device miniaturization and ongoing exploration of shape memory polymers could simplify surgical procedures for implanting such interfaces. Once implanted, wireless strategies for powering and transferring data from the interface can eliminate bulky external wires, reduce infection risk, and enhance day-to-day usability. By outlining the current limitations of neuromuscular interfaces along with potential future directions, this review aims to guide continued research efforts and future collaborations between engineers and specialists in the field of neuromuscular and musculoskeletal medicine.

StairNet: visual recognition of stairs for human-robot locomotion.

Human-robot walking with prosthetic legs and exoskeletons, especially over complex terrains, such as stairs, remains a significant challenge. Egocentric vision has the unique potential to detect the walking environment prior to physical interactions, which can improve transitions to and from stairs. This motivated us to develop the StairNet initiative to support the development of new deep learning models for visual perception of real-world stair environments. In this study, we present a comprehensive overview of the StairNet initiative and key research to date. First, we summarize the development of our large-scale data set with over 515,000 manually labeled images. We then provide a summary and detailed comparison of the performances achieved with different algorithms (i.e., 2D and 3D CNN, hybrid CNN and LSTM, and ViT networks), training methods (i.e., supervised learning with and without temporal data, and semi-supervised learning with unlabeled images), and deployment methods (i.e., mobile and embedded computing), using the StairNet data set. Finally, we discuss the challenges and future directions. To date, our StairNet models have consistently achieved high classification accuracy (i.e., up to 98.8%) with different designs, offering trade-offs between model accuracy and size. When deployed on mobile devices with GPU and NPU accelerators, our deep learning models achieved inference speeds up to 2.8 ms. In comparison, when deployed on our custom-designed CPU-powered smart glasses, our models yielded slower inference speeds of 1.5 s, presenting a trade-off between human-centered design and performance. Overall, the results of numerous experiments presented herein provide consistent evidence that StairNet can be an effective platform to develop and study new deep learning models for visual perception of human-robot walking environments, with an emphasis on stair recognition. This research aims to support the development of next-generation vision-based control systems for robotic prosthetic legs, exoskeletons, and other mobility assistive technologies.

Clinical use of digital applications for diagnostic and treatment planning in prosthodontics: A scoping review.

AIM: This scoping review aimed to compile and evaluate clinical trials investigating digital applications in prosthetic diagnostics and treatment planning by assessing their clinical relevance and future potential. METHODS: Following the PCC-framework for scoping reviews and combining the source of analysis (Population/P: "prosthodontics"), the technique of interest (Concept/C: "digital application") and the field of interest (Context/C: "diagnostics"), a three-pronged search strategy was applied in the database PubMed and Web of Science. Clinical trials (≥10 study participants, English/German) were considered until 2023-03-09. Reporting adhered to the PRISMA-ScR statement. RESULTS: The search identified 520 titles, of which 18 full-texts met the inclusion criteria for data extraction. The trials involved a total of 14,457 study participants and were mapped for prosthetic subdisciplines: fixed (n = 9; 50%) and removable (n = 4; 22%) prosthodontics, reconstructive dentistry in general (n = 3; 17%), and temporo-mandibular joint disorders (n = 2; 11%). Data merging of medical format files, as DICOM+STL, was the dominant digital application (n = 7; 39%); and virtual treatment simulation using digital smile design or digital wax-up represented the most frequent prosthetic diagnostics (n = 6; 33%). CONCLUSION: This scoping review identified a relatively low number of clinical trials. The future potential of digital diagnostics appears to be mostly related to the subdiscipline of fixed prosthodontics, especially regarding virtual treatment simulation for communication with the patient and among dental professionals. Artificial intelligence emerged as a key technology in many of the identified studies. Further research in this area is needed to explore the capabilities of digital technologies in prosthetic diagnostics and treatment planning.

The UK prosthetic and orthotic workforce: current status and implications for the future.

BACKGROUND: Prosthetists and orthotists (POs) are the smallest of the 14 allied health profession (AHP) workforces within NHS England. Obtaining data on the workforce has always been challenging due to this information being held across different organisations. An understanding of the prosthetic and orthotic (P&O) workforce is essential to ensure that it is adequately equipped to meet the evolving needs of users of P&O services. The study aims to estimate the size and composition, for the first time, of the UK P&O workforce and P&O service provision. METHODS: To gather the required information, two surveys (one for the UK P&O workforce and one for UK P&O private company) and two freedom of information (FOI) requests [one for all NHS Trusts and Health Boards (HB) in the UK and one for the higher education institutes in the UK offering programmes leading to registration as a PO were developed and distributed from September to December 2022. RESULTS: The P&O workforce survey received a 74% response rate (863 POs) and 25 private companies reported employing one or more P&O staffing groups. From the FOI requests, 181 of a potential 194 Trusts/Health Boards and all four higher education institutions responded. The study indicated a total of 1766 people in the UK P&O workforce, with orthotists and orthotic technicians representing the largest percentage of the workforce at 32% and 30%, respectively. A greater percentage of prosthetists (65%) and orthotists (57%) were employed by private companies compared to the NHS. Only 34% of POs stated that they "definitely" planned to remain in the workforce for the next 5 years. The current UK PO employment levels are 142 to 477 short of the World Health Organisation's (WHO) recommendation. CONCLUSIONS: The low job satisfaction amongst many POs and the projected increase in the number of people who will require prosthetic and/or orthotic care in the UK are challenges for future UK P&O services. Strategies are required to create a sustainable and resilient workforce that can meet the needs of a changing healthcare landscape.

Neural interfacing architecture enables enhanced motor control and residual limb functionality postamputation.

Despite advancements in prosthetic technologies, patients with amputation today suffer great diminution in mobility and quality of life. We have developed a modified below-knee amputation (BKA) procedure that incorporates agonist-antagonist myoneural interfaces (AMIs), which surgically preserve and couple agonist-antagonist muscle pairs for the subtalar and ankle joints. AMIs are designed to restore physiological neuromuscular dynamics, enable bidirectional neural signaling, and offer greater neuroprosthetic controllability compared to traditional amputation techniques. In this prospective, nonrandomized, unmasked study design, 15 subjects with AMI below-knee amputation (AB) were matched with 7 subjects who underwent a traditional below-knee amputation (TB). AB subjects demonstrated significantly greater control of their residual limb musculature, production of more differentiable efferent control signals, and greater precision of movement compared to TB subjects (P < 0.008). This may be due to the presence of greater proprioceptive inputs facilitated by the significantly higher fascicle strains resulting from coordinated muscle excursion in AB subjects (P < 0.05). AB subjects reported significantly greater phantom range of motion postamputation (AB: 12.47 ± 2.41, TB: 10.14 ± 1.45 degrees) when compared to TB subjects (P < 0.05). Furthermore, AB subjects also reported less pain (12.25 ± 5.37) than TB subjects (17.29 ± 10.22) and a significant reduction when compared to their preoperative baseline (P < 0.05). Compared with traditional amputation, the construction of AMIs during amputation confers the benefits of enhanced physiological neuromuscular dynamics, proprioception, and phantom limb perception. Subjects' activation of the AMIs produces more differentiable electromyography (EMG) for myoelectric prosthesis control and demonstrates more positive clinical outcomes.

The relation between cochlear implant programming levels and speech perception performance in post-lingually deafened adults: a data-driven approach.

PURPOSE: Programming a cochlear implant (fitting) is an essential part of a user's post-implantation journey, defining how sound will be translated into electrical stimulation and aiming to provide optimal speech perception outcomes. Currently, there are no established, evidence-based guidelines for fitting cochlear implant users, leading to a high degree of variability in fitting practices, users' parameters, and probably outcomes. In this study a data-driven approach is used to retrospectively investigate the relation between cochlear implant fitting parameters and speech perception outcomes in post-lingually deafened adults. METHODS: 298 data points corresponding to fitting parameters and speech audiometry test results for the same number of adult, post-lingually deafened, experienced CI users were analyzed. Correlation analysis was performed, after which parameters from the top-scoring and bottom-scoring tertiles were compared via the Mann-Whitney-Wilcoxon u test. RESULTS: Weak correlations between dynamic range and speech audiometry outcomes were identified, having p values lower than (albeit close to) 0.05. A significant (p < 0.05) difference in electrical dynamic range (the difference between the minimum and maximum amount of current which may be delivered by each electrode) was found, with top-scoring subjects having on average a wider dynamic range. CONCLUSION: The association between dynamic range and speech perception outcomes shown in this retrospective study highlights the need for deeper investigation into evidence-driven fitting. It might be a first step in the direction of evidence-based fitting, minimizing variability in outcomes for cochlear implant users and helping mitigate the issue of unexplained low performance.

Building a Multidisciplinary Clinic Dedicated to Upper-Extremity Limb Loss.

Complete care of the patient with upper limb loss mandates a long-term, multifaceted approach. Increased functionality and quality of life require collaborative efforts between the patient's surgeon, prosthetist, hand therapists, mental health professionals, and peers. An individual surgeon may find that initiating and maintaining a practice offering total integrated treatment for upper-extremity amputees is a formidable task, but with specific, actionable recommendations, the process can be demystified. The upper-extremity surgeon must be facile with operative techniques such as targeted muscle reinnervation (TMR), regenerative peripheral nerve interface (RPNI), and soft tissue reconstruction and focus on team recruitment strategy and promotion of the clinic within the community. Consistent communication and team decision-making shape each patient's preoperative and postoperative course. We aim to relay effective interventions at each step of recovery from each clinic member and describe clinic workflow designed to reinforce holistic care. We present a blueprint for creating a functional and comprehensive multidisciplinary center for patients with upper-extremity limb loss for those providers interested in providing care, but who are missing the logistical roadmap for how to do so.

Wavelet Transforms Significantly Sparsify and Compress Tactile Interactions.

As higher spatiotemporal resolution tactile sensing systems are being developed for prosthetics, wearables, and other biomedical applications, they demand faster sampling rates and generate larger data streams. Sparsifying transformations can alleviate these requirements by enabling compressive sampling and efficient data storage through compression. However, research on the best sparsifying transforms for tactile interactions is lagging. In this work we construct a library of orthogonal and biorthogonal wavelet transforms as sparsifying transforms for tactile interactions and compare their tradeoffs in compression and sparsity. We tested the sparsifying transforms on a publicly available high-density tactile object grasping dataset (548 sensor tactile glove, grasping 26 objects). In addition, we investigated which dimension wavelet transform-1D, 2D, or 3D-would best compress these tactile interactions. Our results show that wavelet transforms are highly efficient at compressing tactile data and can lead to very sparse and compact tactile representations. Additionally, our results show that 1D transforms achieve the sparsest representations, followed by 3D, and lastly 2D. Overall, the best wavelet for coarse approximation is Symlets 4 evaluated temporally which can sparsify to 0.5% sparsity and compress 10-bit tactile data to an average of 0.04 bits per pixel. Future studies can leverage the results of this paper to assist in the compressive sampling of large tactile arrays and free up computational resources for real-time processing on computationally constrained mobile platforms like neuroprosthetics.

A Circular, Wireless Surface-Electromyography Array.

Commercial, high-tech upper limb prostheses offer a lot of functionality and are equipped with high-grade control mechanisms. However, they are relatively expensive and are not accessible to the majority of amputees. Therefore, more affordable, accessible, open-source, and 3D-printable alternatives are being developed. A commonly proposed approach to control these prostheses is to use bio-potentials generated by skeletal muscles, which can be measured using surface electromyography (sEMG). However, this control mechanism either lacks accuracy when a single sEMG sensor is used or involves the use of wires to connect to an array of multiple nodes, which hinders patients' movements. In order to mitigate these issues, we have developed a circular, wireless s-EMG array that is able to collect sEMG potentials on an array of electrodes that can be spread (not) uniformly around the circumference of a patient's arm. The modular sEMG system is combined with a Bluetooth Low Energy System on Chip, motion sensors, and a battery. We have benchmarked this system with a commercial, wired, state-of-the-art alternative and found an r = 0.98 (p < 0.01) Spearman correlation between the root-mean-squared (RMS) amplitude of sEMG measurements measured by both devices for the same set of 20 reference gestures, demonstrating that the system is accurate in measuring sEMG. Additionally, we have demonstrated that the RMS amplitudes of sEMG measurements between the different nodes within the array are uncorrelated, indicating that they contain independent information that can be used for higher accuracy in gesture recognition. We show this by training a random forest classifier that can distinguish between 6 gestures with an accuracy of 97%. This work is important for a large and growing group of amputees whose quality of life could be improved using this technology.

Robotic-Enhanced Prosthetic Liners for Vibration Therapy: Reducing Phantom Limb Pain in Transfemoral Amputees.

Phantom limb pain, a common challenge for amputees, lacks effective treatment options. Vibration therapy is a promising non-pharmacologic intervention for reducing pain intensity, but its efficacy in alleviating phantom limb pain requires further investigation. This study focused on developing prosthesis liners with integrated vibration motors to administer vibration therapy for phantom limb pain. The prototypes developed for this study addressed previous issues with wiring the electronic components. Two transfemoral amputees participated in a four-week at-home trial, during which they used the vibration liner and rated their initial and final pain intensity on a numeric rating scale each time they had phantom pain. Semi-structured interviews were conducted to gather feedback following the at-home trial. Both participants described relaxing and soothing sensations in their residual limb and phantom limb while using vibration therapy. One participant reported a relaxation of his phantom limb sensations, while both participants noted a decrease in the intensity of their phantom limb pain. Participants said the vibration liners were comfortable but suggested that the vibration could be stronger and that aligning the contacts could be easier. The results of this study highlight the potential effectiveness of using vibration therapy to reduce the intensity of phantom limb pain and suggest a vibration liner may be a feasible mode of administering the therapy. Future research should address optimizing the performance of the vibration liners to maximize their therapeutic benefits.

Evaluation of Hand Action Classification Performance Using Machine Learning Based on Signals from Two sEMG Electrodes.

Classification-based myoelectric control has attracted significant interest in recent years, leading to prosthetic hands with advanced functionality, such as multi-grip hands. Thus far, high classification accuracies have been achieved by increasing the number of surface electromyography (sEMG) electrodes or adding other sensing mechanisms. While many prescribed myoelectric hands still adopt two-electrode sEMG systems, detailed studies on signal processing and classification performance are still lacking. In this study, nine able-bodied participants were recruited to perform six typical hand actions, from which sEMG signals from two electrodes were acquired using a Delsys Trigno Research+ acquisition system. Signal processing and machine learning algorithms, specifically, linear discriminant analysis (LDA), k-nearest neighbors (KNN), and support vector machines (SVM), were used to study classification accuracies. Overall classification accuracy of 93 ± 2%, action-specific accuracy of 97 ± 2%, and F1-score of 87 ± 7% were achieved, which are comparable with those reported from multi-electrode systems. The highest accuracies were achieved using SVM algorithm compared to LDA and KNN algorithms. A logarithmic relationship between classification accuracy and number of features was revealed, which plateaued at five features. These comprehensive findings may potentially contribute to signal processing and machine learning strategies for commonly prescribed myoelectric hand systems with two sEMG electrodes to further improve functionality.

Accuracy, Repeatability, and Reproducibility of a Hand-Held Structured-Light 3D Scanner across Multi-Site Settings in Lower Limb Prosthetics.

The aim of this work was to assess the accuracy, repeatability, and reproducibility of a hand-held, structured-light 3D scanner (EINScan Pro 2X Plus with High Definition Prime Pack, SHINING 3D Tech. Co., Ltd., Hangzhou, China), to support its potential use in multi-site settings on lower limb prosthetics. Four limb models with different shapes were fabricated and scanned with a metrological 3D scanner (EINScan Laser FreeScan 5X, SHINING 3D Tech. Co., Ltd., Hangzhou, China) by a professional operator (OP0). Limb models were then mailed to three sites where two operators (OP1, OP2) scanned them using their own structured-light 3D scanner (same model). OP1 scanned limb models twice (OP1-A, OP1-B). OP0, OP1-A, and OP2 scans were compared for accuracy, OP1-A and OP1-B for repeatability, and OP1-A and OP2 for reproducibility. Among all comparisons, the mean radial error was <0.25 mm, mean angular error was <4°, and root mean square error of the radial distance was <1 mm. Moreover, limits of agreement were <3.5% for perimeters and volumes. By comparing these results with respect to clinically-relevant thresholds and to the literature available on other 3D scanners, we conclude that the EINScan Pro 2X Plus 3D Scanner with High Definition Prime Pack has good accuracy, repeatability, and reproducibility, supporting its use in multi-site settings.

Simultaneous Three-Degrees-of-Freedom Prosthetic Control Based on Linear Regression and Closed-Loop Training Protocol.

Machine learning-based controllers of prostheses using electromyographic signals have become very popular in the last decade. The regression approach allows a simultaneous and proportional control of the intended movement in a more natural way than the classification approach, where the number of movements is discrete by definition. However, it is not common to find regression-based controllers working for more than two degrees of freedom at the same time. In this paper, we present the application of the adaptive linear regressor in a relatively low-dimensional feature space with only eight sensors to the problem of a simultaneous and proportional control of three degrees of freedom (left-right, up-down and open-close hand movements). We show that a key element usually overlooked in the learning process of the regressor is the training paradigm. We propose a closed-loop procedure, where the human learns how to improve the quality of the generated EMG signals, helping also to obtain a better controller. We apply it to 10 healthy and 3 limb-deficient subjects. Results show that the combination of the multidimensional targets and the open-loop training protocol significantly improve the performance, increasing the average completion rate from 53% to 65% for the most complicated case of simultaneously controlling the three degrees of freedom.

Rehabilitation of Combined Hard and Soft Palate Defects with a Soft Relining Prosthesis: A Clinical Report.

It remains a significant challenge in prosthetic rehabilitation for combined hard and soft palate defects on account of two primary reasons. At first, conventional impressions can hardly get an accurate analogue and usually bring about a terrible experience for the patients. Secondly, conventional hard denture base resins used in obturator prostheses exhibit limitations in marginal sealing, undercut retention, and elastic buffering when in contact with the soft palate. This article presents a case where combined hard and soft palate defects were successfully and rapidly reconstructed by using digital intraoral impression technology and denture soft reline material.

Digital fabrication of custom tracheostomy appliances: A clinical report.

The use of rapid prototyping technology has revolutionized the fabrication of intraoral prostheses. With the advancement of digital technology, its applications have expanded to extraoral prostheses and appliances to replace a variety of head and neck defects. The following clinical report illustrates the use of a new technique that allows the digital replication and recontouring of a stock tracheostomy tube to improve patient fit, comfort, and esthetics.

Automated Determination of Morphometric Parameters of the Human Radius Based on the Results of Its Computed Tomography.

A fundamentally new software method for automated measurement of morphometric parameters of computed tomographic image of the human radius has been designed. The parameters obtained by manual morphometry of computed tomograms using the RadiAnt DICOM Viewer software were compared with the results of the software product developed by us. The relative error in the measurement of morphometric parameters was about 10%. In the future, the presented software method of automated determination of morphometric parameters of the bone will enable modeling of individual prosthesis of the head of the radius based on the results of computed tomograms with consideration of the structural features of the human radius.

[Radiological assessment of long-term outcomes of restorative treatment in patients with shortened dental arches]. / Rentgenologicheskaya otsenka otdalennykh rezul'tatov ortopedicheskogo lecheniya patsientov s ukorochennym zubnym ryadom.

BACKGROUND: Restoring the integrity of the dentition with orthopedic structures should be carried out strictly according to indications, taking into account the condition of the supporting teeth and/or teeth limiting the defect. OBJECTIVE: To conduct a retrospective analysis of the results of orthopedic treatment of patients with shortened dentition according to clinical and radiological methods. MATERIALS AND METHODS: The material for the study was data from cone beam computed tomography (CBCT) of 126 patients with shortened dentition (most patients with the absence of a second molar, as well as the absence of the first and second molars), who sought a consultation about missing teeth in the orthopedic and surgical department of the Federal State Budgetary Institution National Medical Research Center TsNIISiCHLKh Ministry of Health of Russia. RESULTS: At the stages of treatment for patients in the study group, insufficient attention is paid to the restoration of terminal defects of the dentition in the upper and lower jaws, especially the restoration of second molars. This may be due to improper planning of dental treatment and insufficient motivation of the patient to carry out comprehensive dental rehabilitation. According to CT studies, the number of complications of orthopedic treatment in the area of supporting teeth and/or teeth limiting the included defect or terminal defect of the dentition in the masticatory region increases depending on the period of use of the orthopedic structure. CONCLUSIONS: The use of cantilever structures leads to functional overload of the supporting teeth. Neglecting the restoration of a full dentition and prosthetics of end defects of the dentition leads to dentoalveolar advancement of antagonists of missing teeth and the appearance of complications such as functional overload of supporting teeth and resorption of alveolar bone.