BACKGROUND: Patient-specific aiming devices (PSAD) may improve precision and accuracy of glenoid component positioning in total shoulder arthroplasty, especially in degenerative glenoids. The aim of this study was to compare precision and accuracy of guide wire positioning into different glenoid models using a PSAD versus a standard guide.
METHODS: Three experienced shoulder surgeons inserted 2.5 mm K-wires into polyurethane cast glenoid models of type Walch A, B and C (in total 180 models). Every surgeon placed guide wires into 10 glenoids of each type with a standard guide by DePuy Synthes in group (I) and with a PSAD in group (II). Deviation from planned version, inclination and entry point was measured, as well as investigation of a possible learning curve.
RESULTS: Maximal deviation in version in B- and C-glenoids in (I) was 20.3° versus 4.8° in (II) (p < 0.001) and in inclination was 20.0° in (I) versus 3.7° in (II) (p < 0.001). For B-glenoid, more than 50% of the guide wires in (I) had a version deviation between 11.9° and 20.3° compared to ≤ 2.2° in (II) (p < 0.001). 50% of B- and C-glenoids in (I) showed a median inclination deviation of 4.6° (0.0°-20.0°; p < 0.001) versus 1.8° (0.0°-4.0°; p < 0.001) in (II). Deviation from the entry point was always less than 5.0 mm when using PSAD compared to a maximum of 7.7 mm with the standard guide and was most pronounced in type C (p < 0.001).
CONCLUSIONS: PSAD enhance precision and accuracy of guide wire placement particularly for deformed B and C type glenoids compared to a standard guide in vitro. There was no learning curve for PSAD. However, findings of this study cannot be directly translated to the clinical reality and require further corroboration.

BACKGROUND: Endoscopic strip craniectomy followed by helmet therapy (ESCH) is a minimally invasive approach for correcting sagittal craniosynostosis. The treatment involves a patient-specific helmet designed to facilitate lateral growth while constraining sagittal expansion. In this study, finite element modelling was used to predict post-treatment head reshaping, improving our comprehension of the necessary helmet therapy duration.
METHODS: Six patients (aged 11 weeks to 9 months) who underwent ESCH at Connecticut Children\'s Hospital were enrolled in this study. Day-1 post-operative 3D scans were used to create skin, skull, and intracranial volume models. Patient-specific helmet models, incorporating areas for growth, were designed based on post-operative imaging. Brain growth was simulated through thermal expansion, and treatments were modelled according to post-operative Imaging available. Mechanical testing and finite element modelling were combined to determine patient-specific mechanical properties from bone samples collected from surgery. Validation compared simulated end-of-treatment skin surfaces with optical scans in terms of shape matching and cranial index estimation.
RESULTS: Comparison between the simulated post-treatment head shape and optical scans showed that on average 97.3 ± 2.1 % of surface data points were within a distance range of -3 to 3 mm. The cranial index was also accurately predicted (r = 0.91).
CONCLUSIONS: In conclusion, finite element models effectively predicted the ESCH cranial remodeling outcomes up to 8 months postoperatively. This computational tool offers valuable insights to guide and refine helmet treatment duration. This study also incorporated patient-specific material properties, enhancing the accuracy of the modeling approach.

Sagittal craniosynostosis (SC) is a congenital condition whereby the newborn skull develops abnormally owing to the premature ossification of the sagittal suture. Spring-assisted cranioplasty (SAC) is a minimally invasive surgical technique to treat SC, where metallic distractors are used to reshape the newborn\'s head. Although safe and effective, SAC outcomes remain uncertain owing to the limited understanding of skull-distractor interaction and the limited information provided by the analysis of single surgical cases. In this work, an SC population-averaged skull model was created and used to simulate spring insertion by means of the finite-element analysis using a previously developed modelling framework. Surgical parameters were varied to assess the effect of osteotomy and spring positioning, as well as distractor combinations, on the final skull dimensions. Simulation trends were compared with retrospective measurements from clinical imaging (X-ray and three-dimensional photogrammetry scans). It was found that the on-table post-implantation head shape change is more sensitive to spring stiffness than to the other surgical parameters. However, the overall end-of-treatment head shape is more sensitive to spring positioning and osteotomy size parameters. The results of this work suggest that SAC surgical planning should be performed in view of long-term results, rather than immediate on-table reshaping outcomes.

BACKGROUND: ChatGPT (Chat Generative Pre-trained Transformer), developed by OpenAI (San Francisco, CA, USA), has gained attention in the medical field. It has the potential to enhance and simplify tasks, such as preoperative planning in orthopedic surgery. We aimed to test ChatGPT\'s accuracy in measuring the angle of correction for high tibial osteotomy for cases planned and performed at a tertiary teaching hospital in Singapore.
METHODS: Peri-operative angular parameters from 114 consecutive patients who underwent medial opening wedge high tibial osteotomy (MOWHTO) were used to query ChatGPT 3.0. First ChatGPT 3.0 was queried on what information it required to plan a MOWHTO. Based on its response, pre-operative medial proximal tibial angle (MPTA) and joint line congruence angle (JLCA) were provided. ChatGPT 3.0 then responded with its recommended angle of correction. This was compared against the manually planned surgical correction by our fellowship-trained surgeon. A root mean square analysis was then performed to compare ChatGPT 3.0 and manual planning.
RESULTS: The root mean square error (RMSE) of ChatGPT 3.0 in predicting correction angle in MWHTO was 2.96, suggesting a very poor model fit.
CONCLUSIONS: Although ChatGPT 3.0 represents a significant breakthrough in large language models with extensive capabilities, it is not currently optimized to effectively perform complex pre-operative planning in orthopedic surgery, specifically in the context of MOWHTO. Further refinement and consideration of specific factors are necessary to enhance its accuracy and suitability for such applications.

The introduction of three-dimensional (3D) printed anatomical models has garnered interest in pre-operative planning, especially in orthopedic and trauma surgery. Identifying potential error sources and quantifying their effect on the model dimensional accuracy are crucial for the applicability and reliability of such models. In this study, twenty radii were extracted from anatomic forearm specimens and subjected to osteotomy to simulate a defined fracture of the distal radius (Colles\' fracture). Various factors, including two different computed tomography (CT) technologies (energy-integrating detector (EID) and photon-counting detector (PCD)), four different CT scanners, two scan protocols (i.e., routine and high dosage), two different scan orientations, as well as two segmentation algorithms were considered to determine their effect on 3D model accuracy. Ground truth was established using 3D reconstructions of surface scans of the physical specimens. Results indicated that all investigated variables significantly impacted the 3D model accuracy (p < 0.001). However, the mean absolute deviation fell within the range of 0.03 ± 0.20 to 0.32 ± 0.23 mm, well below the 0.5 mm threshold necessary for pre-operative planning. Intra- and inter-operator variability demonstrated fair to excellent agreement for 3D model accuracy, with an intra-class correlation (ICC) of 0.43 to 0.92. This systematic investigation displayed dimensional deviations in the magnitude of sub-voxel imaging resolution for all variables. Major pitfalls included missed or overestimated bone regions during the segmentation process, necessitating additional manual editing of 3D models. In conclusion, this study demonstrates that 3D bone fracture models can be obtained with clinical routine scanners and scan protocols, utilizing a simple global segmentation threshold, thereby providing an accurate and reliable tool for pre-operative planning.

Accurate pre-operative templating of prosthesis components is an essential factor in successful total hip arthroplasty (THA), including robotically-assisted THA (RA-THA) techniques. We sought to validate the accuracy of a novel, robotic-optimized THA planning software compared to a predicate THA planner for component sizing. We analyzed a series of 199 patients who received manual THA (mTHA) and fluoroscopy-based RA-THA at a single institution. All cases were templated using a predicate pre-operative templating software. For RA-THA cases, the novel robotic-optimized pre-operative planner software was also used for templating. The differences between templated and implanted acetabular cup, femoral head, and stem component sizes were compared based on matching within 1, 2, and ≥3 sizes. Differences in templated and implanted femoral stem implant geometry were also compared. The robot-optimized pre-operative RA-THA plans demonstrated equivalent accuracy to that of predicate pre-operative plans for both RA-THA and mTHA cases. Templated acetabular cups (90.4 vs. 86.8 vs. 82.8; p = 0.421), femoral stems (76.0 vs. 65.1 vs. 67.7; p = 0.096), and femoral heads (91.3 vs. 96.2 vs. 88.2; p = 0.302) were within +/-1 size of implanted components. No significant differences were detected in the proportion of matching templated and implanted stem geometry across the study cohorts.

As the field of three-dimensional (3D) visualization rapidly advances, how healthcare professionals perceive and interact with real and virtual objects becomes increasingly complex. Lack of clear vocabulary to navigate the changing landscape of 3D visualization hinders clinical and scientific advancement, particularly within the field of radiology. In this article, we provide foundational definitions and illustrative examples for 3D visualization in clinical care, with a focus on the pediatric patient population. We also describe how understanding 3D visualization tools enables better alignment of hardware and software products with intended use-cases, thereby maximizing impact for patients, families, and healthcare professionals.

This review evaluates the current literature on the recent advances of preoperative planning in the management of complex proximal humerus fractures (PHF). PHFs can pose a considerable challenge for orthopaedic surgeons due to their diversity in presentation and complexity. Poor preoperative planning can lead to prolonged operations, increased blood loss, higher risk of complications, and increased stress on the surgical team. Recent advances have seen the evolution of preoperative planning from conventional methods to computer-assisted virtual surgical technology (CAVST) and three-dimensional (3D) printing, which have been highlighted as transformative tools for improving preoperative planning and postoperative outcomes. CAVST allows the creation of 3D renderings of patient-specific anatomy, clearly demonstrating fracture patterns and facilitating detailed planning for arthroplasty or surgical fixation. The early studies show promising outcomes however the literature calls for more high-quality randomised controlled trials. Using 3D printing for high-fidelity simulation involving patient-specific physical models offers an immersive experience for surgical planning. Preoperative planning with 3D printing reduces operative time, blood loss and use of fluoroscopy. The technology\'s potential to produce customisable surgical implants further improves its versatility. There is a need for a cost analysis for the use of these technologies within the orthopaedic field, particularly considering the high expense of 3D printing materials and extended hospital stays until the printed models are available. CAVST and 3D printing also show promising applications within high-fidelity simulation surgical training, with CAVST offering possibilities in virtual reality and haptic-enhanced simulations and 3D printing providing physical models for trainee surgeons to hone their skills. Moving forward, a reduction in the cost of 3D printing and the advancement of CAVST using artificial intelligence would lead to future improvement. In conclusion, preoperative planning supported by these innovative technologies will play a pivotal role in improving surgical outcomes and training for complex PHF cases.

Background Pre-surgical group and save (G&S) tests are routine but can result in unnecessary expense and theatre delays. The objective of this study was to assess the necessity of G&S testing prior to appendectomy and evaluate the cost implications. Methods This retrospective study analysed the records of 200 patients with appendicitis who underwent emergency appendectomies at a busy general surgery department between March 2021 to August 2022. The study adhered to local clinical governance unit protocol and the Strengthening the Reporting of Cohort Studies in Surgery (STROCCS) guidelines. Patients who had elective appendectomies or other emergency procedures were excluded. Data was collected on age, gender, number of samples and requirement for perioperative transfusion. Comparisons were drawn between patients who underwent laparoscopic, open or converted emergency appendectomies. Results Of the sample population, (median age 32, 55.5% male), 93.5% had valid preoperative G&S tests. None required perioperative blood transfusions. 26% of the patients only required one sample for a valid G&S due to having previous sample in the lab; 55% required two samples; 7% needed a third sample because one initial sample was rejected; and 5.5% required four samples because the initial two samples were rejected. The total cost of these samples was estimated to be £3,500.14. Conclusion Emergency appendectomy poses minimal risk of resulting in the need for blood transfusions. Reevaluating the need for routine preoperative G&S testing and adopting a risk-benefit analysis approach could have a financial benefit for the NHS.

Microperimetry is an emerging technology that provides concurrent analysis of retinal structure and function by combining retinal sensitivity and fixation analysis with fundus imaging. We summarize the substantial evidence validating the evolving role of microperimetry as an adjunctive assessment of visual function in the perioperative setting. We show that microperimetry provides useful complementary information to other established imaging and functional modalities in the perioperative setting for a wide range of vitreoretinal surgical procedures, as well as in cataract and refractive surgeries. This includes preoperative uses such as prognostication of visual and anatomical outcomes, timing of surgical intervention, and assessment of patient suitability for surgery-as well as postoperative uses including quantification of visual recovery, investigation of unexplained postoperative vision loss, and informing expected long term functional outcomes.