Introduction: The efficiency and accuracy of curvature estimation of Cobbs angle provides a powerful index to evaluate the type and severity of scoliosis which would be important for clinical judgement in treatment.
Materials and Methods: An automatic system for measuring spine curvature using the anterior-posterior (AP) view spinal X-ray images was innovated through deep learning by convolutional neural network (CNN) approaches which include the U-Net, the Dense U-Net, and Residual U-Net, to segment the vertebrae. The segmentation results of the vertebrae are reconstructed into a complete segmented spine image, and the spine curvature is calculated based on the Cobbs angle criterion.
Results: For Cobbs angle measurement, we analyze the original U-Net, Residual U-Net, and Dense U-Net which were superior to the other two methods with average Dice similarity coefficient reaching 0.951. The one-way ANOVA analysis between our results and that of two clinicians does not show significant differences.
Discussion: For scoliosis, the classification of spine curve type is complex. With the spine curvature from this automatic system, measurement and analysis of scoliosis will become efficient and accurate. In addition, the segmented results of spinal columns and the spine curvature we acquired from the proposed system in this study may be useful information to apply for another spine-related research.
Conclusions: The proposed system can not only reduce the costs and times of manual measurement but avoid observational error. It can assist doctors in reliable measurement of the spine curvature that is beneficial for better understanding and clinical treatments.

Emerging technologies are reshaping healthcare to align with carbon reduction goals, such as those outlined in the European Green Deal aiming for climate neutrality by 2050. Digital surgical pathways, with their emphasis on patient engagement, not only streamline clinical workflows but also hold promise for reducing carbon emissions and saving time for clinicians and administrators.

During the period from March to August 2023, all lower limb arthroplasty patients at University Hospitals Sussex, a high volume low complication centre were enrolled in a digital surgical care pathway (DCP). This pathway incorporated a web-based health questionnaire for pre-operative assessment, along with digital patient education materials, all validated by pre-assessment nurses.

1060 patients participated in the DCP, leading to significant reductions in carbon emissions. The DCP resulted in a total reduction of 6.84 metric tons of CO2, with 5487.5 kilograms saved from reduced travel and 1358.7 kilograms saved from reduced paper usage. It also led to 282 hours saved for pre operative nurses as 63.9% by identifying appropriateness for telephone consultation.

This is one of the largest prospective studies of the environment benefits of a digital surgical care pathway. It highlights a fundamental transformation in orthopaedic care delivery, driven by a dedication to innovation. Beyond enhancing patient engagement and streamlining clinical workflows, this approach aligns with environmental objectives. As orthopaedic centres continue to pioneer advancements, the integration of digital technologies and environmental consciousness promises to shape a more sustainable and patient-centred healthcare landscape, epitomising the evolution of orthopaedic care in the modern era.

Background: Advancements in artificial intelligence (AI) and natural language processing models have facilitated the development of conversational agents capable of diverse tasks. This study aimed to evaluate and compare the performance of two iterations of ChatGPT, namely ChatGPT 3.5 and ChatGPT 4, to pass the Fellowship of the Royal College of Surgeons (FRCS) Trauma & Orthopaedic Part 1 examination. Methods: A dataset of 140 single best-answer questions from an established surrogate examination for the FRCS Part 1 examination were directly inputted into ChatGPT 3.5 and ChatGPT 4. Each model received identical inputs with no prompt engineering. Results: ChatGPT 4 attained a score of 78.9%, passing the examination and performing significantly better than iteration 3.5, which scored 35.8%, 30% lower than the FRCS pass mark of 65.8%. Analysis of individual question responses demonstrated iteration 4 provided explanatory answers to all questions, with 77.1% of incorrect responses resulting from factual inaccuracy. Iteration 3.5 performed most consistently on questions requiring direct factual recall (59.3% of correct answers) and worst on questions requiring higher-order thinking. Neither version recognised limitations in its knowledge, with iteration 3.5 reporting that it was unable to provide an answer once, while iteration 4 provided explanatory reasoning for all incorrect responses. Conclusion: This study highlights the enhanced capabilities exhibited by ChatGPT compared to its predecessor in passing the FRCS (Trauma & Orthopaedic) Part 1 examination. However, neither iteration of ChatGPT recognises its limitations, and thus, we must accept their fallibilities as much as we applaud their accolades.

Background: Focal chondral defects of the knee can significantly impair patient quality of life. Although different options are available, they are still not conclusive and have several limitations. This study aimed to evaluate the role of autologous cartilage micrografts in the treatment of knee chondropathy. Methods: Eight patients affected by knee chondropathy were evaluated before and after 6 months and 3 years following autologous cartilage micrografts by magnetic resonance imaging (MRI) for cartilage measurement and clinical assessment. Results: All patients recovered daily activities, reporting pain reduction without the need for analgesic therapy; Oxford Knee Score (OKS) was 28.4 ± 6 and 40.8 ± 6.2 and the visual analogue scale (VAS) was 5.5 ± 1.6 and 1.8 ± 0.7 before and after 6 months following treatment, respectively. Both scores remained stable after 3 years. Lastly, a significant improvement of the cartilage thickness was observed using MRI after 3 years. Conclusions: Autologous cartilage micrografts can promote cartilage volume changes, improve symptomatology, and could be a valid approach for the treatment of knee chondropathy.

Avascular necrosis (AVN, osteonecrorsis) of the femoral head is pathologic condition caused by vascular derangement, which very often leads to secondary degenerative changes in hip joint.
Core decompression of the femoral head is well known and widely accepted technique in treating this condition caught in early stages. Traditionally, it is performed under X ray control helping to reach the areas of necrotic tissue located in femoral head. Such approach is based on two dimensional imaging provided by AP and lateral projections which results in lack of precision and possibility of damaging the articular cartilage when performing curettage of the necrotic tissue from underneath.
To accomplish better precision we developed specific aimers. One hand of this aimer was to be positioned intraarticularly over the top of the defect on the femoral head under direct arthroscopic visualization. The other hand was extraarticularly positioned on the standard entering spot under the greater trochanter ridge which is commonly used for placing the guide wire. The rest of procedure was similar to standard core decompression technique.
Construction of the aimer is based on CT scan of the affected hip. Through the sequence of software manipulations 3D model of the patient’s hip is made. It’s being exported in 3D CAD (computer assisted drawing) software. Respecting morphology (shape and dimensions) of particular patient’s hip joint, then the 3D model of the aimer is made . Once finished, the 3D model of the aimer was 3D printed and sterilized for surgical use.

(Introduction) Deep learning (DL) algorithms have been utilized for the diagnosis of medical images. We previously evaluated the thenar muscle atrophy level by measuring the depth of the thenar muscles by ultrasonography (US). The purpose of this study was to detect image features using DL in US images of carpal tunnel syndrome (CTS) and calculate the diagnostic accuracy from the confusion matrix obtained.

(Materials and Methods) US images of 138 hands without CTS and 27 hands diagnosed with CTS were used in this study. Ultrasonographic examination was performed to evaluate the abductor pollicis brevis and opponens pollicis muscles. The transducer was applied onto the palmer surface of the hand perpendicularly to the longitudinal axis of the first metacarpal bone. The short-axis image of the thenar muscle was visualized. Transfer learning was performed using three pre-trained models. The confusion matrix and receiver operating characteristic curves were used to evaluate diagnostic accuracy. Furthermore, regions where DL was determined to be important were visualized.

(Results) The highest score had an accuracy of 0.78, precision of 0.91 and recall of 0.77. AUC obtained ROC curve was 0.90. Visualization of the important features revealed that the DL models focused on the hypoechoic lesion lateral to the bony prominence of the thumb metacarpal bone.

(Conclusion) We analyzed the usefulness of the diagnostic method by DL for US images of the thenar muscle atrophy of CTS. DL could be a useful tool for evaluation of the thenar muscle atrophy.

Background: Robotics is developing by leaps and bounds; Just five years after we began using an active robot for total knee replacement, manufacturers are introducing a new robotic device into clinical practice, the first impressions of which we would like to share in this study. Methods: After a training course, we performed a random series of 85 operations on a new generation of active robot, after which we compared the main time parameters of planning, preparation, and operation. In addition, we surveyed the surgical team using the Spielberger State Anxiety Inventory (STAI) Short Form scale. Results: The planning stage in the new generation of robot is automated and takes on average 14±3 minutes, which is significantly shorter than the previous version with manual image segmentation. The average registration time for the new generation was 13±5 minutes, versus the old generation 22±2 minutes, the average resection time was 31±6 minutes versus 38±9 minutes, which affected the total operating time for the new generation. robot, which is 20.4% higher. Personal anxiety on the STAI scale for the operating staff did not exceed 30 points (average value 25±3); when mastering the technology of old-generation robots, this score ranged from 30 to 45 points (average value 36±8). Conclusions: Thus, the new generation of active robot for total knee replacement saves time in the operating room, and mastering the technology does not affect the psychological state of the staff.

The successful fracture healing in long bones by Internal fixation through Plating is based on developing a stable construct. This stable construct relies upon Bone to Bone contact, Screw to Bone contact, Screw-to-Plate contact and Plate-to-Bone contact. The implant can fail due to the loosening of any such contacts leading to the pulling out of screws with or without the plates. The most vulnerable contact point is screw to bone ( purchase in cortices) , particularly in osteoporotic bones, leading to loosening of screws. The design improvements have been a progressive process by improving bone-to-plate contacts with Low contact plates, Screw plate contact by interlocking, through threaded holes. Despite these improvements in designs, stable fixation of osteoporotic bone remains vulnerable. We hereby introduce an addition to the above concepts for stable construction and have developed screw to screw thread interlocking system. This enables the screw to lock with each other inside the bone, thus minimizing the pull-out of screws due to loss of bone density. In this paper, we discuss the Principle of screw-to-screw interlocking and the Device which is patented ( Indian) as a “Screw Thread Interlocking Plate System ( STIPS)”.

Implantation of the acetabular cup is the cornerstone of total hip arthroplasty (THA). The outcome of THA is related to acetabular inclination and anteversion, as well as other parameters like stability, limb length alignment, capsule closure, etc. Various navigation and robotic equipment are available to assist the surgeon in placing the hip implant in the right version. High cost, steep learning curve, and equipment safety have restricted its use to less than one percent. We have designed an image-free navigation device to assist the surgeon in implanting the acetabular cup in the right inclination and anteversion. The experiment has been performed on an artificial hip bone structure. Historically, 50 iterations of the angle measurements were performed to assess the device's accuracy. The images from each of the measurements were imported in Image J software to find out the actual angle. The principle of OpenCV is used for image processing in our navigation device. We found the angle of inclination mean error of 0.15° with a standard deviation of 0.44°with a p-value <0.05, which is very significant. Similarly, the angle of anteversion mean error was -1.06° with a standard deviation of 0.34° and p-value < 0.05, which is very significant. The tool provides accuracy with an error of less than 1.5-2 degrees. Our image processing device delivered promising results with regard to acetabular inclination and acetabular anteversion in invitro studies. It can be an option in third world countries who do not have access to navigation systems.