Do 3-D Printed Handheld Models Improve Surgeon Reliability for Recognition of Intraarticular Distal Radius Fracture Characteristics?

Are 3D-printed Models of Tibial Plateau Fractures a Useful Addition to Understanding Fractures for Junior Surgeons?

BACKGROUND

Tibial plateau fractures are often complex, and they can be challenging to treat. Classifying fractures is often part of the treatment process, but intra- and interobserver reliability of fracture classification systems often is inadequate to the task, and classifications that lack reliability can mislead providers and result in harm to patients. Three-dimensionally (3D)-printed models might help in this regard, but whether that is the case for the classification of tibial plateau fractures, and whether the utility of such models might vary by the experience of the individual classifying the fractures, is unknown.

QUESTIONS/PURPOSES

(1) Does the overall interobserver agreement improve when fractures are classified with 3D-printed models compared with conventional radiology? (2) Does interobserver agreement vary among attending and consultant trauma surgeons, senior surgical residents, and junior surgical residents? (3) Do surgeons' and surgical residents' confidence and accuracy improve when tibial plateau fractures are classified with an additional 3D model compared with conventional radiology?

METHODS

Between 2012 and 2020, 113 patients with tibial plateau fractures were treated at a Level 1 trauma center. Forty-four patients were excluded based on the presence of bone diseases (such as osteoporosis) and the absence of a CT scan. To increase the chance to detect an improvement or deterioration and to prevent observers from losing focus during the classification, we decided to include 40 patients with tibial plateau fractures. Nine trauma surgeons, eight senior surgical residents, and eight junior surgical residents-none of whom underwent any study-specific pretraining-classified these fractures according to three often-used classification systems (Schatzker, OA/OTA, and the Luo three-column concept), with and without 3D-printed models, and they indicated their overall confidence on a 10-point Likert scale, with 0 meaning not confident at all and 10 absolutely certainty. To set the gold standard, a panel of three experienced trauma surgeons who had special expertise in knee surgery and 10 years to 25 years of experience in practice also classified the fractures until consensus was reached. The Fleiss kappa was used to determine interobserver agreement for fracture classification. Differences in confidence in assessing fractures with and without the 3D-printed model were compared using a paired t-test. Accuracy was calculated by comparing the participants' observations with the gold standard.

RESULTS

The overall interobserver agreement improved minimally for fracture classification according to two of three classification systems (Schatzker: κconv = 0.514 versus κ3Dprint = 0.539; p = 0.005; AO/OTA:κconv = 0.359 versus κ3Dprint = 0.372; p = 0.03). However, none of the classification systems, even when used by our most experienced group of trauma surgeons, achieved more than moderate interobserver agreement, meaning that a large proportion of fractures were misclassified by at least one observer. Overall, there was no improvement in self-assessed confidence in classifying fractures or accuracy with 3D-printed models; confidence was high (about 7 points on a 10-point scale) as rated by all observers, despite moderate or worse accuracy and interobserver agreement.

CONCLUSION

Although 3D-printed models minimally improved the overall interobserver agreement for two of three classification systems, none of the classification systems achieved more than moderate interobserver agreement. This suggests that even with 3D-printed models, many fractures would be misclassified, which could result in misleading communication, inaccurate prognostic assessments, unclear research, and incorrect treatment choices. Therefore, we cannot recommend the use of 3D-printed models in practice and research for classification of tibial plateau fractures.

LEVEL OF EVIDENCE

Level III, diagnostic study.

Musculoskeletal trauma and artificial intelligence: current trends and projections

Musculoskeletal trauma accounts for a significant fraction of emergency department visits and patients seeking urgent care, with a high financial cost to society. Diagnostic imaging is indispensable in the workup and management of trauma patients. However, diagnostic imaging represents a complex multifaceted system, with many aspects of its workflow prone to inefficiencies or human error. Recent technological innovations in artificial intelligence and machine learning have shown promise to revolutionize our systems for providing medical care to patients. This review will provide a general overview of the current state of artificial intelligence and machine learning applications in different aspects of trauma imaging and provide a vision for how such applications could be leveraged to enhance our diagnostic imaging systems and optimize patient outcomes.

A Novel Instant 3-Dimensional Printing System for Postoperative Fracture Patients: A Comparative Cohort Study

Background

Traditional plaster (TP) is a widely used auxiliary fixation (AF) approach for postoperative fracture patients. However, patient discomfort and inconvenience to clinicians has limited its application. We introduce a novel instant 3-dimensional printing appliance system (3D-AS) to address such issues.

Material/Methods

Twenty-seven postoperative fracture patients were divided randomly between a TP group and a 3D-AS group, and analyzed retrospectively. Radiographic images during follow-up were evaluated for fracture healing and fracture reduction quality. The range of motion (ROM) was recorded to assess motor performance. Patient pain was assessed using the Visual Analogue Scale (VAS). Complications were also compared between the 2 groups.

Results

The patients comprised 17 men and 10 women with ages ranging from 21 to 69 years (mean age: 47.35). All patients completed a follow-up visit (range: 14–19 months, mean: 13.59 months). Although no significant difference was found between general characteristics (P>0.05) and the time of fracture union (P>0.05), significant differences between groups were seen in complications (P<0.05), VAS (P<0.01), patient satisfaction (P<0.05), and ROM for the upper joints (P<0.05).

Conclusions

Our study suggests that 3D-AS provides better upper-limb ROM and more comfortable healing for postoperative fracture patients, indicating that it can be recommended for use in such patients.