A key element of the peritalar subluxation (PTS) seen in progressive collapsing foot deformity (PCFD) occurs through the transverse tarsal joint complex. However, the normal and pathological relations of these joints are not well understood. The objective of this study to compare Chopart articular coverages between PCFD patients and controls using weight-bearing computed tomography (WBCT). In this retrospective case control study, 20 patients with PCFD and 20 matched controls were evaluated. Distance and coverage mapping techniques were used to evaluate the talonavicular and calcaneocuboid interfaces. Principal axes were used to divide the talar head into 6 regions (medial/central/lateral and plantar/dorsal) and the calcaneocuboid interface into 4 regions. Repeated selections were performed to evaluate reliability of joint interface identification. Surface selections had high reliability with an ICC > 0.99. Talar head coverage decreases in plantarmedial and dorsalmedial (− 79%, p = 0.003 and − 77%, p = 0.00004) regions were seen with corresponding increases in plantarlateral and dorsolateral regions (30%, p = 0.0003 and 21%, p = 0.002) in PCFD. Calcaneocuboid coverage decreased in plantar and medial regions (− 12%, p = 0.006 and − 9%, p = 0.037) and increased in the lateral region (13%, p = 0.002). Significant subluxation occurs across the medial regions of the talar head and the plantar medial regions of the calcaneocuboid joint. Coverage and distance mapping provide a baseline for understanding Chopart joint changes in PCFD under full weightbearing conditions.

Objective: To assess interobserver reliability of previously described coronal plane rotation measurements of medial column bones and to assess their ability to accurately quantify changes in rotational profile. Methods: Two cadaveric below-knee specimens were implanted with pins in each bone of the medial column. Weight-bearing computed tomography (CT) scans were acquired in a simulated standing position under neutral, supinated, and pronated conditions. For each specimen and condition, 2 observers measured the coronal plane rotation of the navicular, medial cuneiform, first metatarsal base, shaft, and head, and proximal phalanx of the hallux as previously described. The rotation of each pin was measured relative to the ground in the coronal plane for each condition. These measurements were defined as benchmarks for the rotational profile of each bone. The correlation between these benchmarks and direct bone measurements was then assessed. Intraclass correlation coeficiente was used to assess interobserver reliability. Pearson’s coefficient was used to evaluate correlations. Results: The interobserver reliability of direct bone measurements ranged from 0.98 to 0.99. Correlations between pin rotation and direct measurements ranged from ρ=0.87 to 0.99 across the neutral, supinated, and pronated conditions. Conclusion: Coronal plane rotation measurements of medial column bones described in this study are reliable tools. Level of Evidence III; Case-Control Study.

Artificial intelligence (AI) is looked upon nowadays as the potential major catalyst for the fourth industrial revolution. In the last decade, AI use in Orthopaedics increased approximately tenfold. Artificial intelligence helps with tracking activities, evaluating diagnostic images, predicting injury risk, and several other uses. Chat Generated Pre-trained Transformer (ChatGPT), which is an AI-chatbot, represents an extremely controversial topic in the academic community. The aim of this review article is to simplify the concept of AI and study the extent of AI use in Orthopaedics and sports medicine literature. Additionally, the article will also evaluate the role of ChatGPT in scientific research and publications.Level of evidence: Level V, letter to review.

Category: Basic Sciences/Biologics; Hindfoot Introduction/Purpose: Implant-related artifact (IRA) represents an important limitation in Computed Tomography (CT) assessment of osteotomy and fracture healing, bone-implant integration, and success of fusion procedures. Metallic implants are the most used in foot and ankle surgery and are recognized as important IRA generators. Absorbable and bio-integrative (BI) implants are attractive options for bone fixation when postoperative CT imaging is likely, particularly in procedures with higher risk for nonunion. However, the literature comparing IRA with metallic and BI implants is scarce. The objective of this study was to assess the degree of IRA around metallic and BI cannulated screws. Our hypothesis was that BI implants would demonstrate significantly decreased IRA around the inserted screws. Methods: In this cadaveric/CT imaging study, 2 below-knee specimens were used. Medial displacement calcaneal osteotomy was performed through a 5-cm long lateral heel approach. Calcaneal tuberosity was displaced medially by 10mm and fixed provisionally with 2 parallel K-wires under fluoroscopic guidance. Specimens were fixed with two headless 4.0 millimeters cannulated screws, either metallic or BI. Cone-beam CT imaging of both specimens was acquired following osteotomy screw fixation (120kVp, 5.5mA, 0.25mm isotropic). Using a dedicated software, the overall dispersion of Hounsfield units (HU) in a 3D cube of 30mm edge length was assessed. Four HU lines were then traced parallel to the screws, crossing the osteotomy site. Lines 1, 2, 3 and 4 were positioned respectively: In close proximity, over, inside the cannulation and away from the implant. The HU dispersion in these lines was measured and compared between metallic and BI implanted specimens, using T-tests/Wilcoxon analysis. P-values<0.05 were considered significant. Results: When compared to the BI implant, the average HU was pronouncedly and significantly increased around metallic implants in the lines with more close proximity (Line 1), over the screw wall (Line 2) and inside the screw cannulation (Line 3), when considering both the whole line extension inside the 3D cube as well as in a selected 8mm line-segment across the calcaneal osteotomy line: Line 1 (entire, 7.26 vs -159; selected, -5 vs -249) Line 2 (entire, 4.846 vs 108; selected, 6286 vs 151.2); Line 3 (entire, 1664 vs 144; selected, -277.7 vs 198.7) selected). However, across Line 4 (away from the implant), the HU dispersion was interestingly and significantly decreased around the metallic implant (entire, -49 vs 178.5; selected, -110 vs 221), potentially as result of beam hardening artifact, concentrating HU close to the metal, and shielding the surrounding cancellous bone from being accurately reconstructed. Conclusion: In this cadaveric imaging study, we compared Implant-related artifact (IRA) around metallic and bio-integrative (BI) implants utilized to fix medial displacement calcaneal osteotomies. We found metallic implants to demonstrate significantly and pronouncedly increased HU dispersion in in close proximity with the implants and significantly decreased dispersion more distantly from the implant, shielding the surrounding cancellous bone, and potentially hindering the assessment of bone density quality and bone/osteotomy/fusion healing in its neighborhood. BI implants represent an alternative to decrease these IRA effects. Additional clinical studies are needed to confirm and expand our findings.

Computerized clinical decision support systems (CDSS) have evolved rapidly and are causing a radical transformation in healthcare. These systems are integrating artificial intelligence-enabled mechanisms to improve the quality of care, health of populations, and reduce the costs of healthcare. Some of these mechanisms include descriptive, predictive, and prescriptive analytics to assist with clinical decision making. However, there are significant barriers to CDSS adoption, implementation, and acceptance among physicians and clinicians who utilize the systems to provide high-quality patient care. The authors used systematic literature review guidelines to the research questions: “To what extent is data-driven decision making applied in CDSS?” “What prevalent theories are used in data-driven CDSS research?” and “What major system attributes contribute to the theoretical frameworks?”