Effect of Bone Metastasis Cancer Board on Spinal Surgery Outcomes: A Retrospective Study

Background and Objectives: Bone metastasis cancer boards (BMCBs) focusing on the management of bone metastases have been gathering much attention. However, the association of BMCBs with spinal surgery in patients with spinal metastases remains unclear. In this retrospective single-center observational study, we aimed to clarify the effect of a BMCB on spinal metastasis treatment. Materials and Methods: We reviewed consecutive cases of posterior decompression and/or instrumentation surgery for metastatic spinal tumors from 2008 to 2019. The BMCB involved a team of specialists in orthopedics, rehabilitation medicine, radiation oncology, radiology, palliative supportive care, oncology, and hematology. We compared demographics, eastern cooperative oncology group performance status (ECOGPS), Barthel index (BI), number of overall versus emergency surgeries, and primary tumors between patients before (2008-2012) and after (2013-2019) BMCB establishment. Results: A total of 226 patients including 33 patients before BMCB started were enrolled; lung cancer was the most common primary tumor. After BMCB establishment, the mean patient age was 5 years older (p = 0.028), the mean operating time was 34 min shorter (p = 0.025), the mean hospital stay was 34.5 days shorter (p < 0.001), and the mean BI before surgery was 12 points higher (p = 0.049) than before. Moreover, the mean number of surgeries per year increased more than fourfold to 27.6 per year (p < 0.01) and emergency surgery rates decreased from 48.5% to 29.0% (p = 0.041). Patients with an unknown primary tumor before surgery decreased from 24.2% to 9.3% (p = 0.033). Postoperative deterioration rates from 1 to 6 months after surgery of ECOGPS and BI after BMCB started were lower than before (p = 0.045 and p = 0.027, respectively). Conclusion: The BMCB decreased the emergency surgery and unknown primary tumor rate despite an increase in the overall number of spinal surgeries. The BMCB also contributed to shorter operation times, shorter hospital stays, and lower postoperative deterioration rates of ECOGPS and BI.

Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI-A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

BACKGROUND

Rapid quantification of liver metastasis for diagnosis and follow-up is an unmet medical need in patients with secondary liver malignancies. We present a 3D-quantification model of neuroendocrine liver metastases (NELM) using gadoxetic-acid (Gd-EOB)-enhanced MRI as a useful tool for multidisciplinary cancer conferences (MCC).

METHODS

Manual 3D-segmentations of NELM and livers (149 patients in 278 Gd-EOB MRI scans) were used to train a neural network (U-Net architecture). Clinical usefulness was evaluated in another 33 patients who were discussed in our MCC and received a Gd-EOB MRI both at baseline and follow-up examination (n = 66) over 12 months. Model measurements (NELM volume; hepatic tumor load (HTL)) with corresponding absolute (ΔabsNELM; ΔabsHTL) and relative changes (ΔrelNELM; ΔrelHTL) between baseline and follow-up were compared to MCC decisions (therapy success/failure).

RESULTS

Internal validation of the model's accuracy showed a high overlap for NELM and livers (Matthew's correlation coefficient (φ): 0.76/0.95, respectively) with higher φ in larger NELM volume (φ = 0.80 vs. 0.71; p = 0.003). External validation confirmed the high accuracy for NELM (φ = 0.86) and livers (φ = 0.96). MCC decisions were significantly differentiated by all response variables (ΔabsNELM; ΔabsHTL; ΔrelNELM; ΔrelHTL) (p < 0.001). ΔrelNELM and ΔrelHTL showed optimal discrimination between therapy success or failure (AUC: 1.000; p < 0.001).

CONCLUSION

The model shows high accuracy in 3D-quantification of NELM and HTL in Gd-EOB-MRI. The model's measurements correlated well with MCC's evaluation of therapeutic response.