Development and Evaluation of a Rib Statistical Shape Model for Thoracic Surgery.

Patients with advanced cancer undergoing chest wall resection may require reconstruction. Currently, rib prostheses are created by segmenting computed tomography images, which is time-consuming and labour intensive. The aim was to optimise the production of digital rib models based on a patient's age, weight, height and gender. A statistical shape model of human ribs was created and used to synthetise rib models, which were compared to the ones produced by segmentation and mirroring. The segmentation took 11.56±1.60 min compared to 0.027 ±0.009 min using the new technique. The average mesh error between the mirroring technique and segmentation was 0.58±0.25 mm (right ribs), and 0.87±0.18 mm (left ribs), compared to 1.37±0.66 mm ( ) and 1.68 ±0.77 mm ( ), respectively, for the new technique. The new technique is promising for the efficiency and ease-of-use in the clinical environment. Clinical Relevance- This is an optimised 3D modelling method providing clinicians with a time-efficient technique to create patient-specific rib prostheses, without any expertise or software knowledge required.

Digital health: a neglected part of health curricula?

With growing government investment and a thriving consumer market, digital technologies are rapidly transforming our means of healthcare delivery. These innovations offer increased diagnostic accuracy, greater accessibility and reduced costs compared with conventional equivalents. Despite these benefits, implementing digital health poses challenges. Recent surveys of healthcare professionals (HCPs) have revealed marked inequities in digital literacy across the healthcare service, hampering the use of these new technologies in clinical practice. Furthermore, a lack of appropriate training in the associated ethical considerations risks HCPs running into difficulty when it comes to patient rights. In light of this, and with a clear need for dedicated digital health education, we argue that our focus should turn to the foundation setting of any healthcare profession: the undergraduate curriculum.

Chest Wall Reconstruction Using 3-Dimensional Printing: Functional and Mechanical Results.

BACKGROUND: Tumors involving the chest wall may require extensive resection and reconstruction. This study aims to evaluate functional, cosmetic results, and quality of life (QoL) in patients who had a reconstruction based on patient-specific 3-dimensional (3D) printing. METHODS: The patient-specific chest wall prosthesis was created for 10 patients. The anatomical models were 3D printed and used to produce a silicone mold that was filled with methyl methacrylate to create the customized prosthesis. Evaluation of the reconstruction was completed with a QoL assessment and postoperative tracking of patients' chest motion, using infrared markers. The distance between plot points representing markers on the operated and contralateral sides was measured to assess symmetrical motion. RESULTS: Twenty-three consecutive patients were enrolled, with the median age of 64 years. Thirteen patients underwent a nonrigid reconstruction, and 10 had a patient-specific rigid reconstruction with methyl methacrylate. The median number of ribs resected was 3. No postoperative complications or morbidity related to the prostheses were reported. The median hospital stay in the nonrigid reconstruction group was 8.5 days compared with 7.5 days (p = .167) in the rigid reconstruction group. Postoperatively, most patients had low levels of symptoms, with 82% experiencing chest pain and 53% experiencing dyspnea. Rigid reconstruction patients demonstrated more symmetrical breathing motion compared with nonrigid reconstruction patients. The mean distances were 2.32 ± 2.18 and 7.28 ± 5.87 (P < .00001), respectively. CONCLUSIONS: This study shows that a 3D patient-specific prosthesis is feasible and safe, suggesting a possible trend toward improved breathing mechanics, QoL, and cosmetic results.

Harnessing the power of social media to support medical training during COVID-19.

Twitter offers a powerful means to share information, suggest ways to help and highlight useful initiatives during the global COVID-19 pandemic. We describe one successful Twitter campaign focusing on the role of medical students (#MedStudentCovid), led by the volunteer organisation Becoming A Doctor with support from leaders at the General Medical Council, Health Education England, NHS England and the World Health Organization.