Validation of a Web-Based Planning Tool for Percutaneous Cryoablation of Renal Tumors

Abstract

Purpose: To validate a simulation environment for virtual planning of percutaneous cryoablation of renal tumors.

Materials and methods: Prospectively collected data from 19 MR-guided procedures were used for validation of the simulation model. Volumetric overlap of the simulated ablation zone volume (Σ) and the segmented ablation zone volume (S; assessed on 1-month follow-up scan) was quantified. Validation metrics were DICE Similarity Coefficient (DSC; the ratio between twice the overlapping volume of both ablation zones divided by the sum of both ablation zone volumes), target overlap (the ratio between the overlapping volume of both ablation zones to the volume of S; low ratio means S is underestimated), and positive predictive value (the ratio between the overlapping volume of both ablation zones to the volume of Σ; low ratio means S is overestimated). Values were between 0 (no alignment) and 1 (perfect alignment), a value > 0.7 is considered good.

Results: Mean volumes of S and Σ were 14.8 cm³ (± 9.9) and 26.7 cm³ (± 15.0), respectively. Mean DSC value was 0.63 (± 0.2), and ≥ 0.7 in 9 cases (47%). Mean target overlap and positive predictive value were 0.88 (± 0.11) and 0.53 (± 0.24), respectively. In 17 cases (89%), target overlap was ≥ 0.7; positive predictive value was ≥ 0.7 in 4 cases (21%) and < 0.6 in 13 cases (68%). This indicates S is overestimated in the majority of cases.

Conclusion: The validation results showed a tendency of the simulation model to overestimate the ablation effect. Model adjustments are necessary to make it suitable for clinical use.

Keywords: Computer-assisted image processing; Cryosurgery; Intraoperative monitoring; Kidney neoplasms; Preoperative care.

Fig. 1

Workflow of web-based environment

Fig. 2

Startpage of web environment

Fig. 3

Web environment viewer showing MRI in three orthogonal planes. Available image series and tools are shown in bars on the left

Fig. 4

Contrast enhanced, pre-operative axial CT image in corticomedullary phase showing automated segmentation results of kidney (purple) and tumor (pink) in the viewer

Fig. 5

Contrast enhanced, pre-operative axial CT image in corticomedullary phase. Result of automated kidney (purple) and tumor (pink) segmentation are shown. The needles (blue) with original coordinates and simulation result (red) which are registered on to the pre-operative scan are shown as well. The real ablation zone segmented from the 1-month FU scan is shown in yellow (next steps). The simulated ablation zone is overestimated in this case

Fig. 6

Example of segmented kidney (purple) and ablated ablation zone (yellow) on 1-month follow-up MRI scan

Fig. 7

Example of validation case showing the simulated (Σ) ablation zone in green (volume 19.47 cm³) and segmented (S) ablation zone in red (volume 13.64 cm³). Darkgreen represent an overlap between Σ and S (green and red). A small part of the segmented tumor is visible in yellow (white arrow) and is not covered by both S and Σ. Average absolute error is 1.85 mm. DICE similarity coefficient and sensitivity were both scored as excellent with values of 0.8 and 0.95, respectively. Positive predictive value was scored as adequate with a value of 0.67

Fig. 8

Only the simulated ablation zone (S; green) and tumor (yellow) are shown, as would be the case when using the environment for planning purposes

Fig. 9

Example of case with overestimation. The simulated (Σ) ablation zone is shown in green (volume 43.49 cm³) and segmented (S) ablation zone in red (volume 10.95 cm³). Darkgreen represent an overlap between Σ and S (green and red). The needle tracts are visible in the ablation zones. Average absolute error is 6.72 mm. DICE similarity coefficient and positive predictive value were both scored as poor with values of 0.39 and 0.24, respectively. Sensitivity was scored as excellent with a value of 0.97