Purpose: To develop image processing algorithms for noninvasive mapping of microwave thermal ablation using X-ray CT.
Methods: Ten specimens of bovine liver were subjected to microwave ablation (20-80 W, 8 min) while scanned by X-ray CT at 5 s intervals. Specimens were cut and manually traced by two observers. Two algorithms were developed and implemented to map the ablation zone. The first algorithm utilises images segmentation of Hounsfield units changes (ISHU). The second algorithm utilises radial optical flow (ROF). Algorithm sensitivity to spatiotemporal under-sampling was assessed by decreasing the acquisition rate and reducing the number of acquired projections used for image reconstruction in order to evaluate the feasibility of implementing radiation reduction techniques.
Results: The average radial discrepancy between the ISHU and ROF contours and the manual tracing were 1.04±0.74 and 1.16±0.79mm, respectively. When diluting the input data, the ISHU algorithm retained its accuracy, ranging from 1.04 to 1.79mm. By contrast, the ROF algorithm performance became inconsistent at low acquisition rates. Both algorithms were not sensitive to projections reduction, (ISHU: 1.24±0.83mm, ROF: 1.53±1.15mm, for reduction by eight fold). Ablations near large blood vessels affected the ROF algorithm performance (1.83±1.30mm; p < 0.01), whereas ISHU performance remained the same.
Conclusion: The two suggested noninvasive ablation mapping algorithms can provide highly accurate contouring of the ablation zone at low scan rates. The ISHU algorithm may be more suitable for clinical practice as it appears more robust when radiation dose reduction strategies are employed and when the ablation zone is near large blood vessels.
Keywords: Microwave; X-ray CT; noninvasive; thermal ablation; thermal monitoring.