In silico methods to evaluate Fracture Risk and Bone Mineral Density changes in patients undergoing Total Hip Replacement

La sostituzione totale d’anca è uno degli interventi chirurgici con le più alte percentuali di successo. Esistono due varianti di protesi d’anca che differiscono in base al metodo di ancoraggio all’osso: cementate (fissaggio tramite cemento osseo) e non cementate (fissaggio tramite forzamento). Ad oggi, i chirurghi non hanno indicazioni quantitative di supporto per la scelta fra le due tipologie di impianto, decidendo solo in base alla loro esperienza. Due delle problematiche che interessano le protesi non cementate sono la possibilità di frattura intra-operatoria durante l’inserimento forzato e il riassorbimento osseo nel periodo di tempo successivo all’intervento. A partire da rilevazioni densitometriche effettuate su immagini da TC di pazienti sottoposti a protesi d’anca non cementata, sono stati sviluppati due metodi: 1) per la valutazione del rischio di frattura intra-operatorio tramite analisi agli elementi finiti; 2) per la valutazione della variazione di densità minerale ossea (tridimensionalmente attorno alla protesi) dopo un anno dall’operazione. Un campione di 5 pazienti è stato selezionato per testare le procedure. Ciascuno dei pazienti è stato scansionato tramite TC in tre momenti differenti: una acquisita prima dell’operazione (pre-op), le altre due acquisite 24 ore (post 24h) e 1 anno dopo l’operazione (post 1y). I risultati ottenuti hanno confermato la fattibilità di entrambi i metodi, riuscendo inoltre a distinguere e a quantificare delle differenze fra i vari pazienti. La fattibilità di entrambe le metodologie suggerisce la loro possibilità di impiego in ambito clinico: 1) conoscere la stima del rischio di frattura intra-operatorio può servire come strumento di guida per il chirurgo nella scelta dell’impianto protesico ottimale; 2) conoscere la variazione di densità minerale ossea dopo un anno dall’operazione può essere utilizzato come strumento di monitoraggio post-operatorio del paziente

Augmented Reality and Artificial Intelligence in Image-Guided and Robot-Assisted Interventions

In minimally invasive orthopedic procedures, the surgeon places wires, screws, and surgical implants through the muscles and bony structures under image guidance. These interventions require alignment of the pre- and intra-operative patient data, the intra-operative scanner, surgical instruments, and the patient. Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. State of the art approaches often support the surgeon by using external navigation systems or ill-conditioned image-based registration methods that both have certain drawbacks. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only been considered as a visualization device improving traditional workflows. Consequently, the technology is gaining minimum maturity that it requires to redefine new procedures, user interfaces, and interactions. This dissertation investigates the applications of AR, artificial intelligence, and robotics in interventional medicine. Our solutions were applied in a broad spectrum of problems for various tasks, namely improving imaging and acquisition, image computing and analytics for registration and image understanding, and enhancing the interventional visualization. The benefits of these approaches were also discovered in robot-assisted interventions. We revealed how exemplary workflows are redefined via AR by taking full advantage of head-mounted displays when entirely co-registered with the imaging systems and the environment at all times. The proposed AR landscape is enabled by co-localizing the users and the imaging devices via the operating room environment and exploiting all involved frustums to move spatial information between different bodies. The system's awareness of the geometric and physical characteristics of X-ray imaging allows the exploration of different human-machine interfaces. We also leveraged the principles governing image formation and combined it with deep learning and RGBD sensing to fuse images and reconstruct interventional data. We hope that our holistic approaches towards improving the interface of surgery and enhancing the usability of interventional imaging, not only augments the surgeon's capabilities but also augments the surgical team's experience in carrying out an effective intervention with reduced complications

Paediatric fractures of carpal bones other than the scaphoid

OBJECTIVES Fractures of carpal bones other than the scaphoid are rare in children. The aim of this study was to analyze results and identify risk factors for an unfavorable outcome. MATERIAL AND METHODS Children and adolescents up to the age of 16 years who sustained a carpal fracture other than in the scaphoid between 2004 and 2021 were reviewed in this single-center retrospective study. RESULTS In a series of 209 children and adolescents with carpal fractures, 22 had fractures other than the scaphoid. Mean age was 13 years (range 8-16) years, with a total of 41 fractures, with highest incidences for the capitate (10), trapezium (6), triquetrum (4) and pisiform (4). Twenty-nine of these 41 fractures were missed on initial X-ray. Non-displaced fractures were treated with a short arm spica cast including the thumb. Four patients were operated on for displacement fracture or carpometacarpal subluxation. All fractures united, and patients returned to full activities. At the final consultation at a median 14 months (range 6-89) post-injury, all patients with non-displaced fractures were free of symptoms, with excellent Mayo Wrist Scores (MWS). However, three patients with operated trapezium fractures developed early radiological signs of osteoarthritis, two of them with residual pain and MWS rated only good. CONCLUSION Non-displaced pediatric carpal fractures treated by forearm cast have excellent prognosis. Fractures of the trapezium with displacement or first carpometacarpal subluxation incur a risk of osteoarthritis despite anatomical reduction and internal fixation

Automatic image analysis of C-arm Computed Tomography images for ankle joint surgeries

Open reduction and internal fixation is a standard procedure in ankle surgery for treating a fractured fibula. Since fibula fractures are often accompanied by an injury of the syndesmosis complex, it is essential to restore the correct relative pose of the fibula relative to the adjoining tibia for the ligaments to heal. Otherwise, the patient might experience instability of the ankle leading to arthritis and ankle pain and ultimately revision surgery. Incorrect positioning referred to as malreduction of the fibula is assumed to be one of the major causes of unsuccessful ankle surgery. 3D C-arm imaging is the current standard procedure for revealing malreduction of fractures in the operating room. However, intra-operative visual inspection of the reduction result is complicated due to high inter-individual variation of the ankle anatomy and rather based on the subjective experience of the surgeon. A contralateral side comparison with the patient’s uninjured ankle is recommended but has not been integrated into clinical routine due to the high level of radiation exposure it incurs. This thesis presents the first approach towards a computer-assisted intra-operative contralateral side comparison of the ankle joint. The focus of this thesis was the design, development and validation of a software-based prototype for a fully automatic intra-operative assistance system for orthopedic surgeons. The implementation does not require an additional 3D C-arm scan of the uninjured ankle, thus reducing time consumption and cumulative radiation dose. A 3D statistical shape model (SSM) is used to reconstruct a 3D surface model from three 2D fluoroscopic projections representing the uninjured ankle. To this end, a 3D SSM segmentation is performed on the 3D image of the injured ankle to gain prior knowledge of the ankle. A 3D convolutional neural network (CNN) based initialization method was developed and its outcome was incorporated into the SSM adaption step. Segmentation quality was shown to be improved in terms of accuracy and robustness compared to the pure intensity-based SSM. This allows us to overcome the limitations of the previously proposed methods, namely inaccuracy due to metal artifacts and the lack of device-to-patient orientation of the C-arm. A 2D-CNN is employed to extract semantic knowledge from all fluoroscopic projection images. This step of the pipeline both creates features for the subsequent reconstruction and also helps to pre-initialize the 3D-SSM without user interaction. A 2D-3D multi-bone reconstruction method has been developed which uses distance maps of the 2D features for fast and accurate correspondence optimization and SSM adaption. This is the central and most crucial component of the workflow. This is the first time that a bone reconstruction method has been applied to the complex ankle joint and the first reconstruction method using CNN based segmentations as features. The reconstructed 3D-SSM of the uninjured ankle can be back-projected and visualized in a workflow-oriented manner to procure clear visualization of the region of interest, which is essential for the evaluation of the reduction result. The surgeon can thus directly compare an overlay of the contralateral ankle with the injured ankle. The developed methods were evaluated individually using data sets acquired during a cadaver study and representative clinical data acquired during fibular reduction. A hierarchical evaluation was designed to assess the inaccuracies of the system on different levels and to identify major sources of error. The overall evaluation performed on eleven challenging clinical datasets acquired for manual contralateral side comparison showed that the system is capable of accurately reconstructing 3D surface models of the uninjured ankle solely using three projection images. A mean Hausdorff distance of 1.72 mm was measured when comparing the reconstruction result to the ground truth segmentation and almost achieved the high required clinical accuracy of 1-2 mm. The overall error of the pipeline was mainly attributed to inaccuracies in the 2D-CNN segmentation. The consistency of these results requires further validation on a larger dataset. The workflow proposed in this thesis establishes the first approach to enable automatic computer-assisted contralateral side comparison in ankle surgery. The feasibility of the proposed approach was proven on a limited amount of clinical cases and has already yielded good results. The next important step is to alleviate the identified bottlenecks in the approach by providing more training data in order to further improve the accuracy. In conclusion, the new approach presented gives the chance to guide the surgeon during the reduction process, improve the surgical outcome while avoiding additional radiation exposure and reduce the number of revision surgeries in the long term

3D Innovations in Personalized Surgery

Current practice involves the use of 3D surgical planning and patient-specific solutions in multiple surgical areas of expertise. Patient-specific solutions have been endorsed for several years in numerous publications due to their associated benefits around accuracy, safety, and predictability of surgical outcome. The basis of 3D surgical planning is the use of high-quality medical images (e.g., CT, MRI, or PET-scans). The translation from 3D digital planning toward surgical applications was developed hand in hand with a rise in 3D printing applications of multiple biocompatible materials. These technical aspects of medical care require engineers’ or technical physicians’ expertise for optimal safe and effective implementation in daily clinical routines.The aim and scope of this Special Issue is high-tech solutions in personalized surgery, based on 3D technology and, more specifically, bone-related surgery. Full-papers or highly innovative technical notes or (systematic) reviews that relate to innovative personalized surgery are invited. This can include optimization of imaging for 3D VSP, optimization of 3D VSP workflow and its translation toward the surgical procedure, or optimization of personalized implants or devices in relation to bone surgery