A functional model for classifying metastatic lesions integrating scans and biomarkers

Analysis of Magnetic Resonance Imaging Perfusion Parameters for the Identification of Spinal Metastatic Tumors with Rich Blood Supply

PURPOSE

To determine the reliability of dynamic magnetic resonance imaging (MRI) perfusion parameters for the evaluation of blood supply to spinal metastatic tumors.

METHODS

A total of 36 patients with spinal metastasis who underwent dynamic contrast-enhanced magnetic resonance spinal perfusion imaging at Tianjin Hospital from December 2018 to December 2020 were reviewed. Subsequently, the patients underwent corresponding preoperative examination using digital subtraction angiography of the spine at the hospital and were divided into 2 groups accordingly. Differences in dynamic MRI perfusion parameters between the 2 groups were analyzed.

RESULTS

There were statistically significant differences between the 2 groups in the quantitative dynamic contrast-enhanced MRI perfusion parameters vascular permeability and plasma volume, as well as semi-quantitative peak enhancement and blood flow ratio parameters.

CONCLUSIONS

Dynamic MRI perfusion may distinguish spinal metastatic lesions with rich blood supply from those with poor blood supply and may help clinicians identify patients that can benefit from invasive spinal angiography and preoperative embolization. This technique may also provide guidance on decision taking for surgery basing on dynamic MRI perfusion parameters.

Quantile regression-based prediction of intraoperative blood loss in patients with spinal metastases: model development and validation

PURPOSE

To develop and evaluate a quantile regression-based blood loss prediction model for open surgery of spinal metastases.

METHODS

This was a multicenter retrospective cohort study. Over a 11-year period, patients underwent open surgery for spinal metastases at 6 different institutions were reviewed. The outcome measure is intraoperative blood loss (in mL). The effects of baseline, histology of primary tumor and surgical procedure on blood loss were evaluated by univariate and multivariate analysis to determine the predictors. Multivariate ordinary least squares (OLS) regression and 0.75 quantile regression were used to establish two prediction models. The performance of the two models was evaluated in the training set and the test set, respectively.

RESULTS

528 patients were included in this study. Mean age was 57.6 ± 11.2 years, with a range of 20-86 years. Mean blood loss was 1280.1 ± 1181.6 mL, with a range of 10 ~ 10,000 mL. Body mass index (BMI), tumor vascularization, surgical site, surgical extent, total en bloc spondylectomy and microwave ablation use were significant predictors of intraoperative blood loss. Hypervascular tumor, higher BMI, and broader surgical extent were related with massive blood loss. Microwave ablation is more beneficial in surgery with substantial blood loss. Compared to the OLS regression model, the 0.75 quantile regression model may decrease blood loss underestimate.

CONCLUSION

In this study, we developed and evaluated a prediction model for blood loss in open surgery for spinal metastases based on 0.75 quantile regression, which may minimize blood loss underestimate.