Simulation Model of Microsphere Distribution for Selective Internal Radiation Therapy Agrees With Observations

MIDOS: a novel stochastic model towards a treatment planning system for microsphere dosimetry in liver tumors

PURPOSE

Transarterial radioembolization (TARE) procedures treat liver tumors by injecting radioactive microspheres into the hepatic artery. Currently, there is a critical need to optimize TARE towards a personalized dosimetry approach. To this aim, we present a novel microsphere dosimetry (MIDOS) stochastic model to estimate the activity delivered to the tumor(s), normal liver, and lung.

METHODS

MIDOS incorporates adult male/female liver computational phantoms with the hepatic arterial, hepatic portal venous, and hepatic venous vascular trees. Tumors can be placed in both models at user discretion. The perfusion of microspheres follows cluster patterns, and a Markov chain approach was applied to microsphere navigation, with the terminal location of microspheres determined to be in either normal hepatic parenchyma, hepatic tumor, or lung. A tumor uptake model was implemented to determine if microspheres get lodged in the tumor, and a probability was included in determining the shunt of microspheres to the lung. A sensitivity analysis of the model parameters was performed, and radiation segmentectomy/lobectomy procedures were simulated over a wide range of activity perfused. Then, the impact of using different microspheres, i.e., SIR-Sphere®, TheraSphere®, and QuiremSphere®, on the tumor-to-normal ratio (TNR), lung shunt fraction (LSF), and mean absorbed dose was analyzed.

RESULTS

Highly vascularized tumors translated into increased TNR. Treatment results (TNR and LSF) were significantly more variable for microspheres with high particle load. In our scenarios with 1.5 GBq perfusion, TNR was maximum for TheraSphere® at calibration time in segmentectomy/lobar technique, for SIR-Sphere® at 1-3 days post-calibration, and regarding QuiremSphere® at 3 days post-calibration.

CONCLUSION

This novel approach is a decisive step towards developing a personalized dosimetry framework for TARE. MIDOS assists in making clinical decisions in TARE treatment planning by assessing various delivery parameters and simulating different tumor uptakes. MIDOS offers evaluation of treatment outcomes, such as TNR and LSF, and quantitative scenario-specific decisions.

Verification of a method to detect glass microspheres via micro-CT

INTRODUCTION

The ability to determine the microscopic distribution of glass microspheres in ⁹⁰ Y radioembolization has important applications in post-treatment microdosimetry and cluster analysis. Current methods are time-intensive and labor-intensive and thus are typically only applied to small samples.

MATERIALS AND METHODS

A high-resolution micro-CT image with a voxel size of 8.74 µm was acquired of phantoms containing ~25 µm-diameter glass microspheres embedded in tissue-equivalent materials that were optically transparent, which allowed true microsphere locations to be determined using transmission light microscopy. A 3-stage algorithm was developed to estimate the number and locations of microspheres in tissue regions. The stages are thresholding the CT image and discarding regions with insufficient voxels, estimating the number of microspheres in each region using the values of the detected and neighboring region voxels and estimating locations for each microsphere using the outputs of the previous two stages. Two different methods for estimating the number of microspheres in each region were derived, as were five methods for localizing microspheres. Metrics for each stage were computed, and the mean absolute error (MAE) between the dose to 72 µm voxels of the true and estimated dose maps created from the microsphere locations was used as the figure of merit for overall algorithm performance. Microsphere locations identified in the optical micrograph were used as the gold standard for the metrics of all stages. The method's utility was then demonstrated using a specimen from a human neuroendocrine tumor (NET) treated with glass ⁹⁰ Y microspheres.

RESULTS

The stage detecting regions containing microspheres found 100% of microspheres inside regions. The number of incorrectly detected regions without microspheres was 1.5% of the total number of regions. In stage 2, with these parameters, nearly 94% of the actual number of spheres in each region was correctly counted, and only 5% of the estimated sphere quantities in each region were false positives. The MAE between the true dose maps and dose maps estimated using the full algorithm with optimal parameter and method choices was 4.2%. A total of 5,713 glass microspheres were identified as being distributed heterogeneously in the NET specimen with a maximum tumor dose of >2500 Gy and 46% of the specimen receiving <20 Gy.

CONCLUSIONS

This work developed and evaluated a method to detect and estimate the three-dimensional locations of glass microspheres in whole tissue samples that require less manual effort than traditional methods. This method could be used to gain important insights into the heterogeneity of microsphere distributions that would be useful for improving radioembolization treatment planning.

The physics of radioembolization

Radioembolization is an established treatment for chemoresistant and unresectable liver cancers. Currently, treatment planning is often based on semi-empirical methods, which yield acceptable toxicity profiles and have enabled the large-scale application in a palliative setting. However, recently, five large randomized controlled trials using resin microspheres failed to demonstrate a significant improvement in either progression-free survival or overall survival in both hepatocellular carcinoma and metastatic colorectal cancer. One reason for this might be that the activity prescription methods used in these studies are suboptimal for many patients.In this review, the current dosimetric methods and their caveats are evaluated. Furthermore, the current state-of-the-art of image-guided dosimetry and advanced radiobiological modeling is reviewed from a physics' perspective. The current literature is explored for the observation of robust dose-response relationships followed by an overview of recent advancements in quantitative image reconstruction in relation to image-guided dosimetry.This review is concluded with a discussion on areas where further research is necessary in order to arrive at a personalized treatment method that provides optimal tumor control and is clinically feasible.