Artificial-Intelligence-Aided Radiographic Diagnostic of Knee Osteoarthritis Leads to a Higher Association of Clinical Findings with Diagnostic Ratings

Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study

INTRODUCTION

The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent to which recent AI advancements sway career decisions was assessed.

MATERIALS AND METHODS

A digital survey was distributed to student members of orthopaedic societies across Germany, Switzerland, and Austria. Subgroup analyses explored how gender, AI knowledge, and technical inclination shape attitudes towards AI.

RESULTS

Of 174 total respondents, 86.2% (n = 150) intended to pursue a career in orthopaedic surgery and were included in the analysis. The majority (74.5%) reported 'basic' or 'no' knowledge about AI. Approximately 29.3% believed AI would significantly impact orthopaedics within 5 years, with another 35.3% projecting 5-10 years. AI was predominantly seen as an assistive tool (77.8%), without significant fear of job displacement. The most valued AI applications were identified as preoperative implant planning (85.3%), administrative tasks (84%), and image analysis (81.3%). Concerns arose regarding skill atrophy due to overreliance (69.3%), liability (68%), and diminished patient interaction (56%). The majority maintained a 'neutral' view on AI (53%), though 32.9% were 'enthusiastic'. A stronger focus on AI in medical education was requested by 81.9%. Most participants (72.8%) felt recent AI advancements did not alter their career decisions towards or away from the orthopaedic specialty. Statistical analysis revealed a significant association between AI literacy (p = 0.015) and technical inclination (p = 0.003). AI literacy did not increase significantly during medical education (p = 0.091).

CONCLUSIONS

Future orthopaedic surgeons exhibit a favourable outlook on AI, foreseeing its significant influence in the near future. AI literacy remains relatively low and showed no improvement during medical school. There is notable demand for improved AI-related education. The choice of orthopaedics as a specialty appears to be robust against the sway of recent AI advancements.

LEVEL OF EVIDENCE

Cross-sectional survey study; level IV.

Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery

Purpose

The purpose of this study was to evaluate the perspective of orthopaedic surgeons on the impact of artificial intelligence (AI) and to evaluate the influence of experience, workplace setting and familiarity with digital solutions on views on AI.

Methods

Orthopaedic surgeons of the AGA Society for Arthroscopy and Joint Surgery were invited to participate in an online, cross-sectional survey designed to gather information on professional background, subjective AI knowledge, opinion on the future impact of AI, openness towards different applications of AI, and perceived advantages and disadvantages of AI. Subgroup analyses were performed to examine the influence of experience, workplace setting and openness towards digital solutions on perspectives towards AI.

Results

Overall, 360 orthopaedic surgeons participated. The majority indicated average (43.6%) or rudimentary (38.1%) AI knowledge. Most (54.5%) expected AI to substantially influence orthopaedics within 5-10 years, predominantly as a complementary tool (91.1%). Preoperative planning (83.8%) was identified as the most likely clinical use case. A lack of consensus was observed regarding acceptable error levels. Time savings in preoperative planning (62.5%) and improved documentation (81%) were identified as notable advantages while declining skills of the next generation (64.5%) were rated as the most substantial drawback. There were significant differences in subjective AI knowledge depending on participants' experience (p = 0.021) and familiarity with digital solutions (p < 0.001), acceptable error levels depending on workplace setting (p = 0.004), and prediction of AI impact depending on familiarity with digital solutions (p < 0.001).

Conclusion

The majority of orthopaedic surgeons in this survey anticipated a notable positive impact of AI on their field, primarily as an assistive technology. A lack of consensus on acceptable error levels of AI and concerns about declining skills among future surgeons were observed.

Level of Evidence

Level IV, cross-sectional study.

Influence of a Concomitant Medial Meniscus Injury on Knee Joint Function and Osteoarthritis Presence after Anterior Cruciate Ligament Reconstruction

(1) Background: The aim of this study was to investigate how a medial meniscus injury accompanying an anterior cruciate ligament rupture affects the clinical outcome 10 years after ACL reconstruction. (2) Methods: A total of 37 patients who received anterior cruciate ligament reconstruction (ACLR) were included in this retrospective study. Two groups were analyzed at a single follow-up of 10 years: (i) "isolated (ACLR)" (n = 20) and (ii) "ACLR with medial meniscal injury" (n = 17). The following clinical scores were recorded: International Knee Documentation Committee (IKDC), the Knee Injury and Osteoarthritis Outcome Score (KOOS), Lysholm Score and Tegner Activity Score. To determine the degree of osteoarthritis the Kellgren-Lawrence score was used. (3) Results: The "isolated ACLR" study group scored significantly higher (p < 0.05) on the IKDC subjective questionnaire (mean: 88.4) than the "ACLR with medial meniscus injury" group (mean: 81). The KOOS category "activities of daily living" showed significantly better results in the isolated ACLR group (p < 0.05). The "ACLR with medial meniscus injury" group had significantly higher degree of osteoarthritis (p < 0.05). No significant differences were found in all the other clinical scores. (4) Conclusions: The results of this study further indicate that patients with a concomitant medial meniscus injury have slightly more discomfort in everyday life and increased risk of developing osteoarthritis 10 years after surgery.

Spatial analysis of the osteoarthritis microenvironment: techniques, insights, and applications

Osteoarthritis (OA) is a debilitating degenerative disease affecting multiple joint tissues, including cartilage, bone, synovium, and adipose tissues. OA presents diverse clinical phenotypes and distinct molecular endotypes, including inflammatory, metabolic, mechanical, genetic, and synovial variants. Consequently, innovative technologies are needed to support the development of effective diagnostic and precision therapeutic approaches. Traditional analysis of bulk OA tissue extracts has limitations due to technical constraints, causing challenges in the differentiation between various physiological and pathological phenotypes in joint tissues. This issue has led to standardization difficulties and hindered the success of clinical trials. Gaining insights into the spatial variations of the cellular and molecular structures in OA tissues, encompassing DNA, RNA, metabolites, and proteins, as well as their chemical properties, elemental composition, and mechanical attributes, can contribute to a more comprehensive understanding of the disease subtypes. Spatially resolved biology enables biologists to investigate cells within the context of their tissue microenvironment, providing a more holistic view of cellular function. Recent advances in innovative spatial biology techniques now allow intact tissue sections to be examined using various -omics lenses, such as genomics, transcriptomics, proteomics, and metabolomics, with spatial data. This fusion of approaches provides researchers with critical insights into the molecular composition and functions of the cells and tissues at precise spatial coordinates. Furthermore, advanced imaging techniques, including high-resolution microscopy, hyperspectral imaging, and mass spectrometry imaging, enable the visualization and analysis of the spatial distribution of biomolecules, cells, and tissues. Linking these molecular imaging outputs to conventional tissue histology can facilitate a more comprehensive characterization of disease phenotypes. This review summarizes the recent advancements in the molecular imaging modalities and methodologies for in-depth spatial analysis. It explores their applications, challenges, and potential opportunities in the field of OA. Additionally, this review provides a perspective on the potential research directions for these contemporary approaches that can meet the requirements of clinical diagnoses and the establishment of therapeutic targets for OA.

Enhancing Precision and Efficiency in Knee Arthroplasty: A Comparative Analysis of Computer-Assisted Measurements with a Novel Software Tool versus Manual Measurements for Lower Leg Geometry

(1) Background: The aim of this prospective study was to evaluate measurement software in comparison with manual measurements using inter-observer and intra-observer variability on radiographs in the preoperative planning of total knee arthroplasty. (2) Methods: Two independent observers retrospectively measured the mechanical lateral proximal femoral angle (mLPFA), the mechanical lateral distal femoral angle (mLDFA), the joint line convergence angle (JLCA), the mechanical medial proximal tibial angle (mMPTA), the mechanical lateral distal tibial angle (mLDTA), the hip-knee angle or mechanical tibial-femoral axis angle (HKA), and the anatomical-mechanical angle (AMA) on 55 long-leg anteroposterior radiographs manually twice, followed by measurements using dedicated software. Variability between manual and computer-aided planning was assessed, and all measurements were performed a second time after 14 days in order to assess intra-observer variability. (3) Results: Concerning intra-observer variability, no statistically significant difference was observed regarding the software-based measurements. However, significant differences were noted concerning intra-observer variability when measuring the mLDFA and AMA manually. Testing for statistical significance regarding variability between manual and software-based measurements showed that the values varied strongly between manual and computer-aided measurements. Statistically significant differences were detected for mLPFA, mLDFA, mMPTA, and mLPTA on day 1, and mLPFA, mMPTA, and mLPTA on day 15, respectively. (4) Conclusions: Preoperative planning of leg axis angles and alignment using planning software showed less inter- and intra-observer variability in contrast to manual measurements, and results differed with respect to manual planning. We believe that the planning software is more reliable and faster, and we would recommend its use in clinical settings.

Association of AI-determined Kellgren-Lawrence grade with medial meniscus extrusion and cartilage thickness by AI-based 3D MRI analysis in early knee osteoarthritis

The associations among Kellgren-Lawrence (KL) grade, medial meniscus extrusion (MME), and cartilage thickness in knee osteoarthritis (OA) remain insufficiently understood. Our aim was to determine these associations in early to moderate medial tibiofemoral knee OA. We included 469 subjects with no lateral OA from the Kanagawa Knee Study. KL grade was assessed using artificial intelligence (AI) software. The MME was measured by MRI, and the cartilage thickness was evaluated in 18 subregions of the medial femorotibial joint by another AI system. The median MME width was 1.4 mm in KL0, 1.5 mm in KL1, 2.4 mm in KL2, and 6.0 mm in KL3. Cartilage thinning in the medial femur occurred in the anterior central subregion in KL1, expanded inwardly in KL2, and further expanded in KL3. Cartilage thinning in the medial tibia occurred in the anterior and middle external subregions in KL1, expanded into the anterior and middle central subregions in KL2, and further expanded in KL3. The absolute correlation coefficient between MME width and cartilage thickness increased as the KL grade increased in some subregions. This study provides novel insights into the early stages of knee OA and potentially has implications for the development of early intervention strategies.