Is massive hemothorax still an absolute indication for operation in blunt trauma?

Animal model-based simulation training for three emergent and urgent operations of penetrating thoracic injuries

PURPOSE

To develop animal models of penetrating thoracic injuries and to observe the effects of the animal model-based training on improving the trainees' performance for emergent and urgent thoracic surgeries.

METHODS

With a homemade machine, animal models of lung injuries and penetrating heart injuries were produced in porcine and used for training of chest tube drainage, urgent sternotomy, and emergent thoracotomy. Coefficient of variation of abbreviated injury scale and blood loss was calculated to judge the reproducibility of animal models. Five operation teams from basic-level hospitals (group A) and five operation teams from level III hospitals (group B) were included to be trained and tested. Testing standards for the operations were established after thorough literature review, and expert questionnaires were employed to evaluate the scientificity and feasibility of the testing standards. Tests were carried out after the training. Pre- and post-training performances were compared. Post-training survey using 7-point Likert scale was taken to evaluate the feelings of the trainees to these training approaches.

RESULTS

Animal models of the three kinds of penetrating chest injuries were successfully established and the coefficient of variation of abbreviated injury scale and blood loss were all less than 25%. After literature review, testing standards were established, and expert questionnaire results showed that the scientific score was 7.30 ± 1.49, and the feasibility score was 7.50 ± 0.89. Post-training performance was significantly higher in both group A and group B than pre-training performance. Post-training survey showed that all the trainees felt confident in applying the operations and were generally agreed that the training procedure were very helpful in improving operation skills for thoracic penetrating injury.

CONCLUSIONS

Animal model-based simulation training established in the current study could improve the trainees' performance for emergent and urgent thoracic surgeries, especially of the surgical teams from basic-level hospitals.

Could video-assisted thoracoscopic surgery be feasible for blunt trauma patients with massive haemothorax?

INTRODUCTION

The study reviewed the experience of video-assisted thoracoscopic surgery (VATS) for the treatment of massive haemothorax (MHT).

MATERIALS AND METHODS

All adult patients who sustained blunt trauma with a diagnosis of traumatic haemothorax or pneumothorax (ICD9 860; ICD10 S27.0-2), injury to the heart and lungs (ICD9 861; ICD10 S26, S27.3-9), and injury to the blood vessels of the thorax (ICD9 901; ICD10 S25) were queried from the trauma registry between 2014 and 2018. Patients who had chest tube drainage amounts meeting the criteria for MHT and who underwent subsequent operations were eligible for analyses. The patients were divided into VATS or thoracotomy groups based on the surgical modalities. Descriptions and analyses of the two groups were made.

RESULTS

Thirty-eight patients were enroled in the study, including 8 females (21%) and 30 males. The median age was 47.0 (first quartile (Q1) 25.5 and third quartile (Q3) 59.3) years. Twenty-three patients were in the VATS group, six (26%) of whom were converted to thoracotomy. There were no obvious differences in age, sex, pulse rate, or systolic pressure on arrival to the ED or after resuscitation between the two groups. The laboratory data were worse amongst the thoracotomy group, especially the arterial blood gas analysis (ABG) results: pH 7.2 (7.1, 7.3) vs. 7.4 (7.2, 7.4); HCO₃ 14.6 (12.4, 18.7) vs. 19.7 (16.1, 23.9) mEq/L; base excess (BE) -12.6 (-15.8, -7.8) vs. -5.2 (-11.1, -0.9) mEq/L. The PaO₂/FiO₂ ratio was lower in the thoracotomy group (91.4 (68.5, 193.3) vs. 245.3 (95.7, 398.0) mmHg). The thoracotomy group had coagulopathy (INR 1.6 (1.2, 1.9) vs. 1.3 (1.1, 1.4)) and required more blood transfusions (WB and PRBC 36.0 (16.0, 48.0) vs. 12.0 (4.0, 24.0) units; FFP 20.0 (6.0, 50.0) vs. 6.0 (2.0, 20.0) unit). No factors associated with VATS conversion to thoracotomy could be identified.

CONCLUSIONS

VATS could be applied to selected blunt trauma patients with MHT. The major differences between the VATS and thoracotomy groups were coagulopathy, acidosis, PaO₂/FiO₂ ratio < 200 mmHg, or a persistent need for blood transfusion.

A pilot study of deep learning-based CT volumetry for traumatic hemothorax

PURPOSE

We employ nnU-Net, a state-of-the-art self-configuring deep learning-based semantic segmentation method for quantitative visualization of hemothorax (HTX) in trauma patients, and assess performance using a combination of overlap and volume-based metrics. The accuracy of hemothorax volumes for predicting a composite of hemorrhage-related outcomes - massive transfusion (MT) and in-hospital mortality (IHM) not related to traumatic brain injury - is assessed and compared to subjective expert consensus grading by an experienced chest and emergency radiologist.

MATERIALS AND METHODS

The study included manually labeled admission chest CTs from 77 consecutive adult patients with non-negligible (≥ 50 mL) traumatic HTX between 2016 and 2018 from one trauma center. DL results of ensembled nnU-Net were determined from fivefold cross-validation and compared to individual 2D, 3D, and cascaded 3D nnU-Net results using the Dice similarity coefficient (DSC) and volume similarity index. Pearson's r, intraclass correlation coefficient (ICC), and mean bias were also determined for the best performing model. Manual and automated hemothorax volumes and subjective hemothorax volume grades were analyzed as predictors of MT and IHM using AUC comparison. Volume cut-offs yielding sensitivity or specificity ≥ 90% were determined from ROC analysis.

RESULTS

Ensembled nnU-Net achieved a mean DSC of 0.75 (SD: ± 0.12), and mean volume similarity of 0.91 (SD: ± 0.10), Pearson r of 0.93, and ICC of 0.92. Mean overmeasurement bias was only 1.7 mL despite a range of manual HTX volumes from 35 to 1503 mL (median: 178 mL). AUC of automated volumes for the composite outcome was 0.74 (95%CI: 0.58-0.91), compared to 0.76 (95%CI: 0.58-0.93) for manual volumes, and 0.76 (95%CI: 0.62-0.90) for consensus expert grading (p = 0.93). Automated volume cut-offs of 77 mL and 334 mL predicted the outcome with 93% sensitivity and 90% specificity respectively.

CONCLUSION

Automated HTX volumetry had high method validity, yielded interpretable visual results, and had similar performance for the hemorrhage-related outcomes assessed compared to manual volumes and expert consensus grading. The results suggest promising avenues for automated HTX volumetry in research and clinical care.