Blunt Thoracolumbar-Spine Trauma Evaluation in the Emergency Department: A Meta-Analysis of Diagnostic Accuracy for History, Physical Examination, and Imaging

Timing of Spinal Surgery in Polytrauma: The Relevance of Injury Severity, Injury Level and Associated Injuries

STUDY DESIGN

Retrospective database analysis.

OBJECTIVE

Polytraumatized patients with spinal injuries require tailor-made treatment plans. Severity of both spinal and concomitant injuries determine timing of spinal surgery. Aim of this study was to evaluate the role of spinal injury localization, severity and concurrent injury patterns on timing of surgery and subsequent outcome.

METHODS

The TraumaRegister DGU® was utilized and patients, aged ≥16 years, with an Injury Severity Score (ISS) ≥16 and diagnosed with relevant spinal injuries (abbreviated injury scale, AIS ≥ 3) were selected. Concurrent spinal and non-spinal injuries were analysed and the relation between injury severity, concurrent injury patterns and timing of spinal surgery was determined.

RESULTS

12.596 patients with a mean age of 50.8 years were included. 7.2% of patients had relevant multisegmental spinal injuries. Furthermore, 50% of patients with spine injuries AIS ≥3 had a more severe non-spinal injury to another body part. ICU and hospital stay were superior in patients treated within 48 hrs for lumbar and thoracic spinal injuries. In cervical injuries early intervention (<48 hrs) was associated with increased mortality rates (9.7 vs 6.3%).

CONCLUSIONS

The current multicentre study demonstrates that polytrauma patients frequently sustain multiple spinal injuries, and those with an index spine injury may therefore benefit from standardized whole-spine imaging. Moreover, timing of surgical spinal surgery and outcome appear to depend on the severity of concomitant injuries and spinal injury localization. Future prospective studies are needed to identify trauma characteristics that are associated with improved outcome upon early or late spinal surgery.

Pelvic fractures and thoracolumbar spine injury: A critical overlook in high-impact vehicular trauma management

INTRODUCTION

Pelvic fractures (PF) occur in up to 9 % of trauma cases, primarily from high-impact events, and are associated with increased morbidity and mortality due to frequent concomitant injuries. Thoracolumbar (TL) spinal fractures, particularly at the T10-L2 junction, are also common in high-energy trauma but are less frequently examined in association with PF. Missed TL fractures can lead to serious neurological deficits. Although Advanced Trauma Life Support (ATLS) recommends screening for TL fractures in trauma patients, no standardized guidelines exist. This study aims to explore the relationship between PF and TL fractures in trauma patients and to identify key variables associated with these injuries.

METHODS

This retrospective cohort study analyzed data from the 2021 National Trauma Data Bank (NTDB), focusing on patients with PF resulting from high-impact blunt trauma. Patients were identified using ICD-9 codes for pelvic fractures, and those under 18 years of age or with penetrating trauma were excluded. We collected demographic data, injury grading (Injury Severity Score [ISS], Abbreviated Injury Scale [AIS]), and patient outcomes, comparing those with isolated pelvic fractures (IPF) to those with concomitant pelvic and TL fractures (PTLF).

RESULTS

Of the 37,987 patients with PF, 32.4 % (n = 12,318) had concomitant TL fractures. PTLF patients were older (mean age 44.12 vs. 40.12 years, p < 0.001) and exhibited higher ISS and AIS scores compared to IPF patients. The PTLF group had longer hospital stays (14.51 days vs. 9.4 days, p < 0.001) and higher rates of ICU admission (41.4 % vs. 24.0 %, p < 0.001) and mortality (9.5 % vs. 4.3 %, p < 0.001). PTLF patients were less likely to be discharged home (29.5 % vs. 43.5 %, p < 0.001) and more likely to be transferred to rehabilitation or long-term care facilities. Motor vehicle collisions were the most common mechanism of injury, but auto-pedestrian accidents were more frequent in the PTLF group (17.3 % vs. 11.1 %, p < 0.001). Lumbar spine fractures accounted for 70.2 % of TL injuries.

CONCLUSION

Pelvic fractures from high-impact trauma are strongly associated with concomitant TL fractures, which lead to worse clinical outcomes. Routine TL spine screening in these patients is recommended to ensure timely diagnosis and treatment.

Physical modulation of mesenchymal stem cell exosomes: A new perspective for regenerative medicine

Mesenchymal stem cell-derived exosomes (MSC-Exo) offer promising therapeutic potential for various refractory diseases, presenting a novel therapeutic strategy. However, their clinical application encounters several obstacles, including low natural secretion, uncontrolled biological functions and inherent heterogeneity. On the one hand, physical stimuli can mimic the microenvironment dynamics where MSC-Exo reside. These factors influence not only their secretion but also, significantly, their biological efficacy. Moreover, physical factors can also serve as techniques for engineering exosomes. Therefore, the realm of physical factors assumes a crucial role in modifying MSC-Exo, ultimately facilitating their clinical translation. This review focuses on the research progress in applying physical factors to MSC-Exo, encompassing ultrasound, electrical stimulation, light irradiation, intrinsic physical properties, ionizing radiation, magnetic field, mechanical forces and temperature. We also discuss the current status and potential of physical stimuli-affected MSC-Exo in clinical applications. Furthermore, we address the limitations of recent studies in this field. Based on this, this review provides novel insights to advance the refinement of MSC-Exo as a therapeutic approach in regenerative medicine.

Diagnostic Value of Hounsfield Units for Osteoporotic Thoracolumbar Vertebral Non-Compression Fractures in Elderly Patients with Low-Energy Injuries

Background

Thoracolumbar vertebral fractures are common pathological fractures caused by osteoporosis in the elderly. These fractures are challenging to detect. This study aimed to evaluate the diagnostic value of Hounsfield units for osteoporotic thoracolumbar vertebral non-compression fractures in elderly patients with low-energy fractures.

Methods

The retrospective case-control study included elderly patients diagnosed with osteoporotic thoracolumbar vertebral fractures and non-fractured patients who underwent computed tomography examinations for lumbar vertebra issues during July 2017 and June 2020.

Results

This study included 216 patients with fractures (38 males and 178 females; average age: 77.28±8.68 years) and 124 patients without fractures (21 males and 103 females; average age: 75.35±9.57 years). The difference in Hounsfield units of the target (intermediate) vertebral body significantly differed between the two groups (54.74 ± 21.84 vs 5.86 ± 5.14; p<0.001). The ratios of Hounsfield units were also significantly different between the two groups (1.38 ± 1.60 vs 0.13 ± 0.23; p<0.001). The cut-off value for the difference in Hounsfield units to detect osteoporotic spine fractures was 25.35, with high sensitivity (98.5%), specificity (99.9%), and the area under the curve (AUC) (0.999, 95% CI: 0.999-1). The cut-off value for the odds ratio of Hounsfield units was 0.260, with high sensitivity (99.1%), specificity (92.7%), and AUC (0.970, 95% CI: 0.949-0.992).

Conclusion

The difference between Hounsfield units and the odds ratio of Hounsfield units might help diagnose osteoporotic thoracolumbar vertebral non-compression fractures in elderly patients with low-energy fractures.

Diagnostic Clinical Tool in Trauma Patients to Rule out Thoracolumbar Fracture

Introduction

The primary objective of this study was to assess the effectiveness of the clinical decision tool (CDT) in trauma patients, providing a comparable ability to rule out thoracolumbar (TL) fractures as traditional imaging methods. The goal is to facilitate early clearance of the TL spine without an immediate requirement for radiological tests, thereby minimizing unnecessary utilization of TL-spine imaging.

Methods

A prospective, observational study was conducted on trauma patients with suspected TL injury. To achieve early TL clearance, the CDT assessed criteria such as absence of pain, tenderness, and pain-free axial movement and flexion. The study enrolled alert trauma patients with thoracic and/or lumbar spine injuries, defined by the Glasgow Coma Scale of 15. The study excluded patients not aligning with CDT criteria, such as those who received intravenous opioid analgesia within 4 h and those unable to stand due to suspected pelvic or lower limb injuries.

Results

Following the completion of the CDT steps, there were 31 true negative cases, signifying the absence of TL fractures according to both CDT and imaging studies. The sensitivity of the CDT was 99.38% (95% confidence interval [CI]: 96.59%-99.98%), specificity 9.1% (95% CI: 6.30%-12.73%), negative predictive value (NPV) 96.87% (95% CI: 81.02%-99.56%), positive predictive value (PPV) 34.19% (95% CI: 33.38%-35.00%), negative likelihood ratio (LHR) 0.07 (95% CI: 0.01-0.49), and positive LHR 1.09 (95% CI: 1.06-1.13). The sensitivity, specificity, NPV, PPV, negative LHR, and positive LHR varied with each step in the CDT. Notably, the overall sensitivity was high; however, the stepwise sensitivity decreased, albeit with an improvement in specificity with each further step in the tool. The overall sensitivity in the study cohort (n = 500) was high; however, the stepwise sensitivity decreased, albeit with an improvement in the specificity.

Conclusions

The CDT to rule out TL fracture is a feasible bedside stepwise tool in fully awake trauma patients after a thorough clinical neurological examination on arrival. The tool could help Level II or III trauma centers avoid secondary triage to the higher center.

Straight Leg Raise Cannot Replace Computed Tomography in the Detection of Spinal Column Fractures

INTRODUCTION

An active straight leg raise (SLR) is a weight bearing test which assesses pain upon movement and a patient's ability to load their pelvis, lumbar, and thoracic spine. Since many stable patients undergo computed tomography (CT) scanning solely for spinal tenderness, our hypothesis is that performing active straight leg raising could effectively rule out lumbar and thoracic vertebral fractures.

METHODS

Blunt trauma patients ≥18 years of age with Glasgow Coma Scale 15 presenting in hemodynamically stable condition were screened. Patients remaining in the supine position were asked to perform SLR at 12, 18, and 24 inches above the bed. The patient's ability to raise the leg, baseline pain, and pain at each level were assessed. Patients also underwent standard CT scanning of the chest, abdomen and pelvis. The clinical examination results were then matched post hoc with the official radiology reports.

RESULTS

99 patients were screened, 65 males and 34 females. Spinal fractures were present in 15/99 patients (16%). Mechanisms of injury included motor vehicle collision 51%, pedestrian struck 25%, fall1 9%, and other 4%. The median pain score of patients with and without significant spinal fractures at 12, 18, 24 inches was 7.5, 7, 6 and 5, 5, 4, respectively. At 24 inches, active SLR had sensitivity of 0.47, a specificity of 0.59, a positive predictive value of 0.17, and an negative predictive value of 0.86.

CONCLUSIONS

Although SLR has been discussed as a useful adjunct to secondary survey and physical exam following blunt trauma, its positive and more importantly negative predictive value are insufficient to rule out spinal column fractures. Liberal indications for CT based upon mechanism and especially pain and tenderness are necessary to identify all thoraco-lumbar spine fractures.

Multidisciplinary and Coordinated Management of Osteoporotic Vertebral Compression Fractures: Current State of the Art

Osteoporotic vertebral compression fractures (OVCFs) present a significant health concern, affecting a substantial portion of the older adult population worldwide. This narrative review explores the prevalence, diagnostic challenges and management strategies for OVCFs. Despite the increasing incidence and impact on morbidity and mortality, existing clinical guidelines lack consistency and clear diagnostic and therapeutic recommendations. The review addresses key questions faced by physicians dealing with older adult patients experiencing acute back pain, offering insights into triage, radiological assessments and classification systems. We propose a comprehensive algorithm for clearing OVCF, considering clinical presentation, radiological findings and morphological aspects. Emphasis is placed on the importance of medically treating osteoporosis alongside OVCF management. The review encompasses relevant literature from 1993 to 2023, provides a detailed discussion on triage issues and incorporates a clinically oriented classification system developed by the German Society for Orthopaedics and Trauma. The Material and Methods section outlines the extensive literature search carried out in PUBMED, encompassing clinical and experimental studies, systematic reviews and meta-analyses. The articles retained focused mainly on answering critical questions regarding radiological assessments, imaging modalities and the presence of a specific classification system for OVCFs. The review emphasises that the evaluation and management of OVCFs necessitates a multidisciplinary approach involving spine specialists and bone disease experts. It also addresses the role of conservative versus surgical treatments, with a focus on percutaneous vertebral augmentation. The conclusion summarises the algorithm derived for use in emergency departments and general practice, aiming to streamline OVCF management, reduce unnecessary examinations and ensure optimal patient care. The algorithm recommends primary diagnosis using computed tomography, with magnetic resonance imaging reserved for specific cases. The review advocates a holistic approach, integrating medical and surgical interventions to address the complex challenges posed by OVCFs in ageing populations.

Supplementary value and diagnostic performance of computed tomography scout view in the detection of thoracolumbar spine injuries

PURPOSE

Assessing the diagnostic performance and supplementary value of whole-body computed tomography scout view (SV) images in the detection of thoracolumbar spine injuries in early resuscitation phase and identifying frequent image quality confounders.

METHODS

In this retrospective database analysis at a tertiary emergency center, three blinded senior experts independently assessed SV to detect thoracolumbar spine injuries. The findings were categorized according to the AO Spine classification system. Confounders impacting SV image quality were identified. The suspected injury level and severity, along with the confidence level, were indicated. Diagnostic performance was estimated using the caret package in R programming language.

RESULTS

We assessed images of 199 patients, encompassing 1592 vertebrae (T10-L5), and identified 56 spinal injuries (3.5%). Among the 199 cases, 39 (19.6%) exhibited at least one injury in the thoracolumbar spine, with 12 (6.0%) of them displaying multiple spinal injuries. The pooled sensitivity, specificity, and accuracy were 47%, 99%, and 97%, respectively. All experts correctly identified the most severe injury of AO type C. The most common image confounders were medical equipment (44.6%), hand position (37.6%), and bowel gas (37.5%).

CONCLUSION

SV examination holds potential as a valuable supplementary tool for thoracolumbar spinal injury detection when CT reconstructions are not yet available. Our data show high specificity and accuracy but moderate sensitivity. While not sufficient for standalone screening, reviewing SV images expedites spinal screening in mass casualty incidents. Addressing modifiable factors like medical equipment or hand positioning can enhance SV image quality and assessment.

Deep learning-driven diagnosis of multi-type vertebra diseases based on computed tomography images

Background

Osteoporotic vertebral compression fractures (OVCFs) are the most common type of fragility fracture. Distinguishing between OVCFs and other types of vertebra diseases, such as old fractures (OFs), Schmorl's node (SN), Kummell's disease (KD), and previous surgery (PS), is critical for subsequent surgery and treatment. Combining with advanced deep learning (DL) technologies, this study plans to develop a DL-driven diagnostic system for diagnosing multi-type vertebra diseases.

Methods

We established a large-scale dataset based on the computed tomography (CT) images of 1,051 patients with OVCFs from Luhe Hospital and used data of 46 patients from Xuanwu Hospital as alternative hospital validation dataset. Each patient underwent one examination. The dataset contained 11,417 CT slices and 19,718 manually annotated vertebrae with diseases. A two-stage DL-based system was developed to diagnose five vertebra diseases. The proposed system consisted of a vertebra detection module (VDModule) and a vertebra classification module (VCModule).

Results

The training and testing dataset for the VDModule consisted of 9,135 and 3,212 vertebrae, respectively. The VDModule using the ResNet18-based Faster region-based convolutional neural network (R-CNN) model achieved an area under the curve (AUC), false-positive (FP) rate, and false-negative (FN) rate of 0.982, 1.52%, and 1.33%, respectively, in the testing dataset. The training dataset for VCModule consisted of 14,584 and 47,604 diseased and normal vertebrae, respectively. The testing dataset consisted of 4,489 and 15,122 diseased and normal vertebrae, respectively. The ResNet50-based VCModule achieved an average sensitivity and specificity of 0.919 and 0.995, respectively, in diagnosing four kinds of vertebra diseases except for SN in the testing dataset. In the alternative hospital validation dataset, the ResNet50-based VCModule achieved an average sensitivity and specificity of 0.891 and 0.989, respectively, in diagnosing four kinds of vertebra diseases except for SN.

Conclusions

Our proposed DL system can accurately diagnose four vertebra diseases and has strong potential to facilitate the accurate and rapid diagnosis of vertebral diseases.

Diagnostic accuracy of clinical examination to identify life- and limb-threatening injuries in trauma patients

BACKGROUND

Timely and accurate identification of life- and limb-threatening injuries (LLTIs) is a fundamental objective of trauma care that directly informs triage and treatment decisions. However, the diagnostic accuracy of clinical examination to detect LLTIs is largely unknown, due to the risk of contamination from in-hospital diagnostics in existing studies. Our aim was to assess the diagnostic accuracy of initial clinical examination for detecting life- and limb-threatening injuries (LLTIs). Secondary aims were to identify factors associated with missed injury and overdiagnosis, and determine the impact of clinician uncertainty on diagnostic accuracy.

METHODS

Retrospective diagnostic accuracy study of consecutive adult (≥ 16 years) patients examined at the scene of injury by experienced trauma clinicians, and admitted to a Major Trauma Center between 01/01/2019 and 31/12/2020. Diagnoses of LLTIs made on contemporaneous clinical records were compared to hospital coded diagnoses. Diagnostic performance measures were calculated overall, and based on clinician uncertainty. Multivariate logistic regression analyses identified factors affecting missed injury and overdiagnosis.

RESULTS

Among 947 trauma patients, 821 were male (86.7%), median age was 31 years (range 16-89), 569 suffered blunt mechanisms (60.1%), and 522 (55.1%) sustained LLTIs. Overall, clinical examination had a moderate ability to detect LLTIs, which varied by body region: head (sensitivity 69.7%, positive predictive value (PPV) 59.1%), chest (sensitivity 58.7%, PPV 53.3%), abdomen (sensitivity 51.9%, PPV 30.7%), pelvis (sensitivity 23.5%, PPV 50.0%), and long bone fracture (sensitivity 69.9%, PPV 74.3%). Clinical examination poorly detected life-threatening thoracic (sensitivity 48.1%, PPV 13.0%) and abdominal (sensitivity 43.6%, PPV 20.0%) bleeding. Missed injury was more common in patients with polytrauma (OR 1.83, 95% CI 1.62-2.07) or shock (systolic blood pressure OR 0.993, 95% CI 0.988-0.998). Overdiagnosis was more common in shock (OR 0.991, 95% CI 0.986-0.995) or when clinicians were uncertain (OR 6.42, 95% CI 4.63-8.99). Uncertainty improved sensitivity but reduced PPV, impeding diagnostic precision.

CONCLUSIONS

Clinical examination performed by experienced trauma clinicians has only a moderate ability to detect LLTIs. Clinicians must appreciate the limitations of clinical examination, and the impact of uncertainty, when making clinical decisions in trauma. This study provides impetus for diagnostic adjuncts and decision support systems in trauma.

Spinal injury in major trauma: Epidemiology of 1104 cases from an Italian first level trauma center

INTRODUCTION

Traumatic spinal injuries are frequent and their management is debated, especially in major trauma patients. This study aims to describe a large population of major trauma patients with vertebral fractures to improve prevention measures and fracture management.

PATIENTS AND METHODS

Retrospective analysis of 6274 trauma patients prospectively collected between October 2010 and October 2020. Collected data include demographics, mechanism of trauma, type of imaging, fracture morphology, associated injuries, injury severity score (ISS), survival, and death timing. The statistical analysis focused on mechanism of trauma and the search of predictive factors for critical fractures.

RESULTS

Patients showed a mean age of 47 years and 72.5% were males. Trauma included 59.9% of road accidents and 35.1% of falls. 30.7% patients had at least a severe fracture, while 17.2% had fractures in multiple spinal regions. 13.7% fractures were complicated by spinal cord injury (SCI). The mean ISS of the total population was 26.4 (SD 16.3), with 70.7% patients having an ISS≥16. There is a higher rate of severe fractures in fall cases (40.1%) compared to RA (21.9% to 26.3%). The probability of a severe fracture increased by 164% in the case of fall and by 77% in presence of AIS≥3 associated injury of head/neck while reduced by 34% in presence of extremities associated injuries. Multiple level injuries increased with ISS rise and in the case of extremities associated injuries. The probability of a severe upper cervical fracture increased by 5.95 times in the presence of facial associated injuries. The mean length of stay was 24.7 days and 9.6% of patients died.

CONCLUSIONS

In Italy, road accidents are still the most frequent trauma mechanism and cause more cervico-thoracic fractures, while falls cause more lumbar fractures. Spinal cord injuries represent an indicator of more severe trauma. In motorcyclists or fallers/jumpers, there is a higher risk of severe fractures. When a spinal injury is diagnosed, the probability of a second vertebral fracture is consistent. These data could help the decisional workflow in the management of major trauma patients with vertebral injury.

Epidemiology, injury pattern and outcome of older trauma patients: A 15-year study of level-I trauma centers

BACKGROUND

Older adults have become a significant portion of the trauma population. Exploring their specificities is crucial to better meet their specific needs. The primary objective was to evaluate the temporal changes in the incidence, demographic and trauma characteristics, injury pattern, in-hospital admission, complications, and outcome of older trauma patients.

METHODS

A multicenter retrospective cohort study was conducted using the Quebec Trauma Registry. Patients aged ≥16 years admitted to one of the three adult level-I trauma centers between 2003 and 2017 were included. Descriptive analyses and trend-tests were performed to describe temporal changes.

RESULTS

A total of 53,324 patients were included, and 24,822 were aged ≥65 years. The median [IQR] age increased from 57[36-77] to 67[46-82] years, and the proportion of older adults rose from 41.8% in 2003 to 54.1% in 2017. Among those, falls remain the main mechanism (84.7%-88.3%), and the proportion of severe thorax (+8.9%), head (+8.7%), and spine (+5%) injuries significantly increased over time. The proportion of severely injured older patients almost doubled (17.6%-32.3%), yet their mortality decreased (-1.0%). Their average annual bed-days consumption also increased (+15,004 and +1,437 in non-intensive care wards and ICU, respectively).

CONCLUSIONS

Since 2014, older adults have represented the majority of admissions in Level-I trauma centers in Québec. Their bed-days consumption has greatly increased, and their injury pattern and severity have deeply evolved, while we showed a decrease in mortality.

Artificial Intelligence Accurately Detects Traumatic Thoracolumbar Fractures on Sagittal Radiographs

Background and Objectives: Commonly being the first step in trauma routine imaging, up to 67% fractures are missed on plain radiographs of the thoracolumbar (TL) spine. The aim of this study was to develop a deep learning model that detects traumatic fractures on sagittal radiographs of the TL spine. Identifying vertebral fractures in simple radiographic projections would have a significant clinical and financial impact, especially for low- and middle-income countries where computed tomography (CT) and magnetic resonance imaging (MRI) are not readily available and could help select patients that need second level imaging, thus improving the cost-effectiveness. Materials and Methods: Imaging studies (radiographs, CT, and/or MRI) of 151 patients were used. An expert group of three spinal surgeons reviewed all available images to confirm presence and type of fractures. In total, 630 single vertebra images were extracted from the sagittal radiographs of the 151 patients—302 exhibiting a vertebral body fracture, and 328 exhibiting no fracture. Following augmentation, these single vertebra images were used to train, validate, and comparatively test two deep learning convolutional neural network models, namely ResNet18 and VGG16. A heatmap analysis was then conducted to better understand the predictions of each model. Results: ResNet18 demonstrated a better performance, achieving higher sensitivity (91%), specificity (89%), and accuracy (88%) compared to VGG16 (90%, 83%, 86%). In 81% of the cases, the “warm zone” in the heatmaps correlated with the findings, suggestive of fracture within the vertebral body seen in the imaging studies. Vertebras T12 to L2 were the most frequently involved, accounting for 48% of the fractures. A4, A3, and A1 were the most frequent fracture types according to the AO Spine Classification. Conclusions: ResNet18 could accurately identify the traumatic vertebral fractures on the TL sagittal radiographs. In most cases, the model based its prediction on the same areas that human expert classifiers used to determine the presence of a fracture.

Patients with combined pelvic and spinal injuries have worse clinical and operative outcomes than patients with isolated pelvic injuries analysis of the German Pelvic Registry

Background

Pelvic fractures are often associated with spine injury in polytrauma patients. This study aimed to determine whether concomitant spine injury influence the surgical outcome of pelvic fracture.

Methods

We performed a retrospective analysis of data of patients registered in the German Pelvic Registry between January 2003 and December 2017. Clinical characteristics, surgical parameters, and outcomes were compared between patients with isolated pelvic fracture (group A) and patients with pelvic fracture plus spine injury (group B). We also compared apart patients with isolated acetabular fracture (group C) versus patients with acetabular fracture plus spine injury (group D).

Results

Surgery for pelvic fracture was significantly more common in group B than in group A (38.3% vs. 36.6%; p = 0.0002), as also emergency pelvic stabilizations (9.5% vs. 6.7%; p < 0.0001). The mean time to emergency stabilization was longer in group B (137 ± 106 min vs. 113 ± 97 min; p < 0.0001), as well as the mean time until definitive stabilization of the pelvic fracture (7.3 ± 4 days vs. 5.4 ± 8.0 days; p = 0.147). The mean duration of treatment and the morbidity and mortality rates were all significantly higher in group B (p < 0.0001). Operation time was significantly shorter in group C than in group D (176 ± 81 min vs. 203 ± 119 min, p < 0.0001). Intraoperative blood loss was not significantly different between the two groups with acetabular injuries. Although preoperative acetabular fracture dislocation was slightly less common in group D, postoperative fracture dislocation was slightly more common. The distribution of Matta grades was significantly different between the two groups. Patients with isolated acetabular injuries were significantly less likely to have neurological deficit at discharge (94.5%; p < 0.0001). In-hospital complications were more common in patients with combined spine plus pelvic injuries (groups B and D) than in patients with isolated pelvic and acetabular injury (groups A and C).

Conclusions

Delaying definitive surgical treatment of pelvic fractures due to spinal cord injury appears to have a negative impact on the outcome of pelvic fractures, especially on the quality of reduction of acetabular fractures.

Thoracic Spine Fractures with Blunt Aortic Injury: Incidence, Risk Factors, and Characteristics

Background: The coexistence of thoracic fractures and blunt aortic injury (BAI) is potentially catastrophic and easy to be missed in acute trauma settings. Data regarding patients with thoracic fractures complicated with BAI are limited. Methods: The authors conducted a prospective, observational, single-center study including patients with thoracic burst fractures. A multivariate logistic regression model was developed to determine the risk factors of aortic injury. Results: In total, 124 patients with burst fractures of the thoracic spine were included. The incidence of BAI was 11.3% (14/124) in patients with thoracic burst fractures. Among these patients, 11 patients with BAI were missed diagnoses. The main risk factors of BAI were as follows: Injury severity score (OR 1.184; 95% CI, 1.072–1.308; p = 0.001), mechanism of injury, such as crush (OR 10.474; 95% CI, 1.905–57.579; p = 0.007), flail chest (OR = 4.917; 95% CI, 1.122–21.545; p = 0.035), and neurological deficit (OR = 8.299; 95% CI, 0.999–68.933; p = 0.05). Conclusions: BAI (incidence 11.3%) is common in patients with burst fractures of the thoracic spine and is an easily missed diagnosis. We must maintain a high suspicion of injury for BAI when patients with thoracic burst fractures present with these high-risk factors.

Posterior Ligamentous Complex Injuries of the Thoracolumbar Spine: Importance and Surgical Implications

The soft tissues surrounding the spine play a primordial role in its stability, the most important of which are located posteriorly and are deemed the posterior ligamentous complex (PLC). Injuries to the PLC in the setting of thoracolumbar trauma are often dreaded and little attention has been given to them in the management protocols of thoracolumbar trauma. This review aims to summarize and contextualize current concepts in PLC injuries of the thoracolumbar spine with the aim to provide a clear guide for clinical management. Injuries to the PLC may be suspected on the clinical exam but are often missed, leading to serious complications, including instability and neurological compromise. The diagnosis is often made indirectly by spinal radiographs and CT-scanning or by direct visualization of soft tissues via magnetic resonance imaging. The latter remains the standard imaging modality and is mandatory for patients with a high suspicion of PLC injury. PLC injuries are associated with vertebral fractures and follow a progressive pattern of severity, depending on the mechanism of injury and extent of trauma. Surgical management is warranted, as PLC damage renders the spine unstable. Although fusion was once the standard of care and remains applicable for certain patients, recent endeavors of temporary spinal fixation without fusion are increasingly gaining traction in patients with PLC injuries. In conclusion, PLC injuries are challenging as they are often missed, poorly understood, and are not easily managed. Proper diagnosis and management are crucial to avoid long-standing complications such as spinal instability. Considering the paucity of available data on such an important topic in thoracolumbar trauma, this review article aims to contextualize current concepts in PLC injuries in order to demystify this sparsely covered subject.

Injury characteristics, initial clinical status, and severe injuries associated with spinal fractures in a retrospective cohort of 506 trauma patients

BACKGROUND

Our aim was to describe the characteristics of vertebral fractures, the presence of associated injuries, and clinical status within the first days in a severe trauma population.

METHODS

All patients with severe trauma admitted to our level 1 trauma center between January 2015 and December 2018 with a vertebral fracture were analyzed retrospectively. The fractures were determined by the AO Spine classification as stable (A0, A1, and A2 types) or unstable (A3, A4, B, and C types). Clinical status was defined as stable, intermediate, or unstable based on clinicobiological parameters and anatomic injuries. Severe extraspinal injuries and emergent procedures were studied. Three groups were compared: stable fracture, unstable fracture, and spinal cord injury (SCI) group.

RESULTS

A total of 425 patients were included (mean ± SD age, 43.8 ± 19.6 years; median Injury Severity Score, 22 [interquartile range, 17-34]; 72% male); 72 (17%) in the SCI group, 116 (27%) in the unstable fracture group, and 237 (56%) in the stable fracture group; 62% (95% confidence interval [CI], 57-67%) had not a stable clinical status on admission (unstable, 30%; intermediate, 32%), regardless of the group (p = 0.38). This decreased to 31% (95% CI, 27-35%) on day 3 and 23% (95% CI, 19-27%) on day 5, regardless of the group (p = 0.27 and p = 0.25). Progression toward stable clinical status between D1 and D5 was 63% (95% CI, 58-68%) overall but was statistically lower in the SCI group. Severe extraspinal injuries (85% [95% CI, 82-89%]) and extraspinal emergent procedures (56% [95% CI, 52-61%]) were comparable between the three groups. Only abdominal injuries and hemostatic procedures significantly differed significantly (p = 0.003 and p = 0.009).

CONCLUSION

More than the half of the patients with severe trauma had altered initial clinical status or severe extraspinal injuries that were not compatible with safe early surgical management for the vertebral fracture. These observations were independent of the stability of the fracture or the presence of an SCI.

LEVEL OF EVIDENCE

Prognostic and epidemiological, level III.

Yield of whole-body computed tomography at a low-volume emergency department: A 5-year experience

Objectives:

To share our experience with immediate whole-body computed tomography (WBCT) imaging for trauma patients and to determine its association with surgical intervention and hospital admission.

Methods:

This retrospective observational study included 208 trauma patients who presented to the emergency department and underwent WBCT at the King Abdulaziz University Hospital, Jeddah, Saudi Arabia between January 2014 and November 2018. We excluded pregnant patients and those who went into traumatic cardiac arrest or died before imaging.

Results:

Of all included patients, 48.6% were adults and 72.1% had positive findings; of these, 36.7% of patients were admitted for observation and 27.3% underwent operative interventions.

Conclusion:

Whole-body computed tomography is a useful tool to detect significant traumatic injuries in patients presenting to the emergency department. Moreover, it may assist physicians in determining the disposition of these patients. A clear set of criteria should be established to determine which trauma patients require WBCT imaging during initial resuscitation.

Can a Deep-learning Model for the Automated Detection of Vertebral Fractures Approach the Performance Level of Human Subspecialists?

BACKGROUND

Vertebral fractures are the most common osteoporotic fractures in older individuals. Recent studies suggest that the performance of artificial intelligence is equal to humans in detecting osteoporotic fractures, such as fractures of the hip, distal radius, and proximal humerus. However, whether artificial intelligence performs as well in the detection of vertebral fractures on plain lateral spine radiographs has not yet been reported.

QUESTIONS/PURPOSES

(1) What is the accuracy, sensitivity, specificity, and interobserver reliability (kappa value) of an artificial intelligence model in detecting vertebral fractures, based on Genant fracture grades, using plain lateral spine radiographs compared with values obtained by human observers? (2) Do patients' clinical data, including the anatomic location of the fracture (thoracic or lumbar spine), T-score on dual-energy x-ray absorptiometry, or fracture grade severity, affect the performance of an artificial intelligence model? (3) How does the artificial intelligence model perform on external validation?

METHODS

Between 2016 and 2018, 1019 patients older than 60 years were treated for vertebral fractures in our institution. Seventy-eight patients were excluded because of missing CT or MRI scans (24% [19]), poor image quality in plain lateral radiographs of spines (54% [42]), multiple myeloma (5% [4]), and prior spine instrumentation (17% [13]). The plain lateral radiographs of 941 patients (one radiograph per person), with a mean age of 76 ± 12 years, and 1101 vertebral fractures between T7 and L5 were retrospectively evaluated for training (n = 565), validating (n = 188), and testing (n = 188) of an artificial intelligence deep-learning model. The gold standard for diagnosis (ground truth) of a vertebral fracture is the interpretation of the CT or MRI reports by a spine surgeon and a radiologist independently. If there were any disagreements between human observers, the corresponding CT or MRI images would be rechecked by them together to reach a consensus. For the Genant classification, the injured vertebral body height was measured in the anterior, middle, and posterior third. Fractures were classified as Grade 1 (< 25%), Grade 2 (26% to 40%), or Grade 3 (> 40%). The framework of the artificial intelligence deep-learning model included object detection, data preprocessing of radiographs, and classification to detect vertebral fractures. Approximately 90 seconds was needed to complete the procedure and obtain the artificial intelligence model results when applied clinically. The accuracy, sensitivity, specificity, interobserver reliability (kappa value), receiver operating characteristic curve, and area under the curve (AUC) were analyzed. The bootstrapping method was applied to our testing dataset and external validation dataset. The accuracy, sensitivity, and specificity were used to investigate whether fracture anatomic location or T-score in dual-energy x-ray absorptiometry report affected the performance of the artificial intelligence model. The receiver operating characteristic curve and AUC were used to investigate the relationship between the performance of the artificial intelligence model and fracture grade. External validation with a similar age population and plain lateral radiographs from another medical institute was also performed to investigate the performance of the artificial intelligence model.

RESULTS

The artificial intelligence model with ensemble method demonstrated excellent accuracy (93% [773 of 830] of vertebrae), sensitivity (91% [129 of 141]), and specificity (93% [644 of 689]) for detecting vertebral fractures of the lumbar spine. The interobserver reliability (kappa value) of the artificial intelligence performance and human observers for thoracic and lumbar vertebrae were 0.72 (95% CI 0.65 to 0.80; p < 0.001) and 0.77 (95% CI 0.72 to 0.83; p < 0.001), respectively. The AUCs for Grades 1, 2, and 3 vertebral fractures were 0.919, 0.989, and 0.990, respectively. The artificial intelligence model with ensemble method demonstrated poorer performance for discriminating normal osteoporotic lumbar vertebrae, with a specificity of 91% (260 of 285) compared with nonosteoporotic lumbar vertebrae, with a specificity of 95% (222 of 234). There was a higher sensitivity 97% (60 of 62) for detecting osteoporotic (dual-energy x-ray absorptiometry T-score ≤ -2.5) lumbar vertebral fractures, implying easier detection, than for nonosteoporotic vertebral fractures (83% [39 of 47]). The artificial intelligence model also demonstrated better detection of lumbar vertebral fractures compared with detection of thoracic vertebral fractures based on the external dataset using various radiographic techniques. Based on the dataset for external validation, the overall accuracy, sensitivity, and specificity on bootstrapping method were 89%, 83%, and 95%, respectively.

CONCLUSION

The artificial intelligence model detected vertebral fractures on plain lateral radiographs with high accuracy, sensitivity, and specificity, especially for osteoporotic lumbar vertebral fractures (Genant Grades 2 and 3). The rapid reporting of results using this artificial intelligence model may improve the efficiency of diagnosing vertebral fractures. The testing model is available at http://140.113.114.104/vght_demo/corr/. One or multiple plain lateral radiographs of the spine in the Digital Imaging and Communications in Medicine format can be uploaded to see the performance of the artificial intelligence model.

LEVEL OF EVIDENCE

Level II, diagnostic study.

Thoracic vertebrae fracture: Is it an indicator of abdominal injury?

PURPOSE

Traumatic vertebral fracture accounts for 10-15% of trauma related admissions. While the correlation between lumbar vertebral fractures and abdominal injuries is well established, the relationship between thoracic vertebral fractures (TVF) and abdominal injuries is comparatively less well elucidated. Using a large national trauma database, we aimed to examine the incidence and severity of associated abdominal injuries in blunt trauma patients suffering from TVF.

METHODS

A retrospective cohort study using the Israeli National Trauma Registry was conducted. Patients with thoracic vertebrae spine fractures following blunt mechanisms of trauma between 1997 and 2018 were examined, comparing the incidence and severity of associated intraabdominal organs injuries with and without TVF. Demographics and outcomes between the two cohorts were compared.

RESULTS

From 362,924 blunt trauma patients, 4967 (1.37%) had isolated TVF. Mean age was 49.8 years and 61.9% were males. The most common mechanism of injury was fall following by MVC. The patients with TVF had significantly higher rates of increased ISS score (ISS > 16, 28.45% vs. 10.42%, p < 0.001) and higher mortality rate (3.5% vs. 2%, p < 0.0001). Patients with TVF had 2-3 times more intraabdominal organ injuries (p < 0.001). The most commonly injured organ was spleen (3.28%); followed by liver (2.64%) and kidney (1.47%). An analysis of non-isolated thoracic spine fractures showed same distribution in age, ISS, mechanisms, patterns of intra-abdominal injury, mortality rate and laparotomy rate.

CONCLUSION

Clinicians should have an elevated suspicion for intra-abdominal injuries when a thoracic spine fracture is identified, which may necessitate further evaluation.

Highly reduced-dose CT of the lumbar spine in a human cadaver model

Purpose

Feasibility of a highly reduced-dose lumbar spine CT protocol using iterative reconstruction (IR) in a human cadaver model.

Materials and methods

The lumbar spine of 20 human cadavers was repeatedly examined using three different reduced-dose protocols (RDCT) with decreasing reference tube current-exposure time products (RDCT-1: 50 mAs; RDCT-2: 30 mAs; RDCT-3: 10 mAs) at a constant tube voltage of 140 kV. A clinical standard-dose protocol (SDCT) served as the reference (reference tube current–exposure time product: 70 mAs; tube voltage: 140 kV). Images were reconstructed using filtered back projection (FBP) and two increasing levels of IR: IRL4 and IRL6. A five-point scale was used by two observers to assess the diagnostic quality of anatomical structures (cortical and trabecular bone, intervertebral foramina, pedicles and intervertebral joints, spinous and transverse processes). Objective image noise (OIN) was measured. Results were interpreted using a linear mixed-effects regression model.

Results

RDCT-2 with IRL6 (1.2 ± 0.5mSv) was the lowest reduced-dose protocol which provided diagnostically acceptable and equivalent image quality compared to the SDCT (2.3 ± 1.1mSV) with FBP (p > 0.05). All RDCT protocols achieved a significant reduction of the mean (±SD) effective radiation doses (RDCT-1: 1.7±0.9mSv; RDCT-2: 1.2±0.5mSv; RDCT-3: 0.4±0.2mSv; p < 0.05) compared to SDCT. OIN was lower in all RDCT protocols with the application of IRL4 and IRL6, compared to the SDCT with FBP (p < 0.05).

Conclusion

Highly reduced-dose lumbar spine CT providing diagnostically acceptable image quality is feasible using IR in this cadaver model and may be transferred into a clinical setting.

Emergent Comprehensive Imaging of the Major Trauma Patient: A New Paradigm for Improved Clinical Decision-Making

Modern advances in the medical imaging layered onto sophisticated trauma resuscitation strategies in highly organized regionalized trauma systems have created a paradigm shift in the management of severely injured patients. Although immediate exploratory surgery to identify and control life-threatening injuries still has its place, accelerated image acquisition and interpretation procedures now make it rare for trauma surgeons in major centers to venture into damage control surgery unaided by computed tomography (CT) or other imaging, particularly in cases of blunt trauma. Indeed, because of the high incidence of clinically occult injuries associated with major mechanism trauma, and even lower energy trauma in frail or elderly patients, CT imaging has become as invaluable as physical examination, if not more so, in critical decision-making in support of optimal outcomes. In particular, whole-body computed tomography (WBCT) completed promptly after initial assessment of a major trauma provides a quick, comprehensive survey of injuries that enables better surgical planning, obviates the need for multiple subsequent studies, and permits specialized reconstructions when needed. For those at risk for problematic occult injury after modest trauma, WBCT facilitates safer discharge planning and simplified follow-up. Through standardized guidelines, streamlined protocols, synoptic reporting, accessible web-based platforms, and active collaboration with clinicians, radiologists dedicated to trauma and emergency imaging enable clearer understanding of complex injuries in high-risk patients which leads to superior clinical decision-making. Whereas dated dogma has long warned that the CT scanner is the last place to take a challenging trauma patient, modern practice suggests that, more often than not, early comprehensive imaging can be done safely and efficiently and is in the patient's best interest. This article outlines how the role of diagnostic imaging for major trauma has evolved considerably in recent years.

Prevalence of Fractures and Diagnostic Accuracy of Emergency X-ray in Older Adults Sustaining a Low-Energy Fall: A Retrospective Study

BACKGROUND

Plain radiography (XR) series are standard of care for detection of fall-related fractures in older patients with low-energy falls (LEF) in the emergency department (ED). We have investigated the prevalence of fractures and diagnostic accuracy of XR imaging in the ED.

METHODS

2839 patients with LEF, who were presented to two urban level I trauma centers in 2016 and received XR and computed tomography (CT), were consecutively included in this retrospective cohort study. The primary endpoint was the prevalence of fractures of the vertebral column, rib cage, pelvic ring, and proximal long bones. Secondary endpoints were diagnostic accuracy of XR for fracture detection with CT as reference standard and cumulative radiation doses applied.

RESULTS

Median age was 82 years (range 65-105) with 64.1% female patients. Results revealed that 585/2839 (20.6%) patients sustained fractures and 452/2839 (15.9%) patients received subsequent XR and CT examinations of single body regions. Cross-tabulation analysis revealed sensitivity of XR of 49.7%, a positive likelihood ratio of 27.6, and negative likelihood ratio of 0.5.

CONCLUSIONS

XR is of moderate diagnostic accuracy for ruling-out fractures of the spine, pelvic ring, and rib cage in older patients with LEF. Prospective validations are required to investigate the overall risk-benefit of direct CT imaging strategies, considering the trade-off between diagnostic safety, health care costs, and radiation exposure.