Chronic Osteomyelitis of Long Bones: Imaging Pearls and Pitfalls in Pediatrics

Large-Scale assessment of ChatGPT's performance in benign and malignant bone tumors imaging report diagnosis and its potential for clinical applications

Objective

This study was designed to delve into the complexities involved in diagnosing of benign and malignant bone tumors and to assess the potential of AI technologies like ChatGPT in improving diagnostic accuracy and efficiency. The study also explores the few-shot learning as a method to optimize ChatGPT's performance in specialized medical domains such as benign and malignant bone tumors diagnosis.

Methods

A total of 1366 benign and malignant bone tumors-related imaging reports were collected and diagnosed by 25 experienced physicians. The gold standard of diagnosis was established by combining clinical, imaging and pathological principles.These reports were then input into the ChatGPT model which underwent a few-shot learning method to generate diagnostic results. The diagnostic results of the physicians and the AI model were compared to evaluate the performance of ChatGPT. An experiment was conducted to assess the influence of different radiologist's reporting styles on the model's diagnostic performance. Furthermore, in-depth analysis of misdiagnosed cases was carried out, categorizing diagnostic errors and exploring possible causes.

Results

The diagnostic results generated by ChatGPT showed an accuracy of 0.73, sensitivity of 0.95, and specificity of 0.58. After few-shot learning, ChatGPT demonstrated significant improvement, achieving an accuracy of 0.87, sensitivity of 0.99, and specificity of 0.73, bringing it much closer to the level of physician diagnostics. In an experiment analyzing the influence of the radiologist's reporting style, the model demonstrated higher sensitivity when interpreting reports written by high-level radiologists. In 56 benign cases, ChatGPT misdiagnosed them as malignant. Among these, 35 benign lesions- fibrous dysplasia and osteofibrous dysplasia- were incorrectly identified as metastatic tumors or osteosarcomas; 8 cases of myositis ossificans were wrongly diagnosed as extraosseous osteosarcoma. 7 cases of giant cell tumor of bone at the end of long bone were misdiagnosed as osteosarcoma by intermediate doctors. Chondroblastoma was misdiagnosed as malignant tumor in 6 cases -2 osteosarcoma and 4 chondrosarcoma-In this study, 23 osteosarcoma cases were misdiagnosed by ChatGPT as osteomyelitis; Chondrosarcoma was misdiagnosed as fibrous dysplasia or aneurysmal bone cyst in 8 cases. Four cases of spinal chordoma were misdiagnosed as spinal tuberculosis.

Conclusion

Our findings highlight the potential of ChatGPT in the diagnosis of benign and malignant bone tumors, offering advantages like enhanced efficiency and a reduction in missed diagnoses. However, the necessity of collaborative interactions between physicians and ChatGPT in practical settings was underscored. With an examination into AI's capacity in benign and malignant bone tumors diagnosis, this study lays the groundwork for future AI advancements in medicine. Additionally, the benefits of few-shot learning in fine-tuning ChatGPT applications in specialized fields were also demonstrated.

3D-printed β-TCP/S53P4 bioactive glass scaffolds coated with tea tree oil: Coating optimization, in vitro bioactivity and antibacterial properties

Bone infection treatment is a significant challenge for the orthopedic field. 3D printing is a promising technology to produce scaffolds with customized architecture, able to stimulate and support bone growth. β-TCP and S53P4 bioactive glass (BG) are well-known biomaterials for scaffold manufacturing. However, a multifunctional scaffold, able to inhibit microbial proliferation at the defect site, is of increasing interest to avoid infection recurrence. Tea tree oil (TTO) has aroused interest as an antimicrobial agent to minimize the use of antibiotics. Therefore, combining the regenerative potential of a bioceramic with TTO's antimicrobial properties could result in a scaffold capable of stimulating tissue growth and treating infections. In this context, this study aimed to produce and characterize 3D-printed β-TCP/S53P4 BG scaffolds coated with TTO. Scaffolds morphological and chemical characterizations were carried out through XDR, SEM, and FTIR analysis. β-TCP/S53P4 BG scaffolds showed a compressive strength of ~2 MPa and 53 ± 2% of porosity. The scaffolds were coated by two different procedures, using an ethanol/TTO (EtOH/TTO) and a gelatin/TTO (Gel/TTO) solution with 5, 10, and 15% (v/v) TTO. The addition of TTO decreased MG-63 cell viability for both coating groups, but the Gel/TTO group showed higher cell viability. The antibacterial activity of the coated scaffolds was evaluated against S. aureus and higher inhibition of colony formation was found for Gel/TTO group. Therefore, the coating with Gel/TTO was effective in terms of antibacterial activity and cell viability. Such Gel/TTO coated β-TCP/S53P4 BG scaffolds are proposed for antibacterial bone tissue engineering.