scholarly journals Manual versus automated image fusion of real-time ultrasonography and MR/CT images for radiofrequency ablation of hepatic tumors: Results of a randomized prospective trial

2020 ◽  
Author(s):  
Moon Hyung Choi ◽  
JOON-IL CHOI ◽  
Young Joon Lee
Keyword(s):  
Radiofrequency Ablation ◽  
Image Fusion ◽  
Real Time ◽  
Prospective Trial ◽  
Ct Images ◽  
Hepatic Tumors ◽  
Randomized Prospective Trial ◽  
Real Time Ultrasonography

scholarly journals Full-Automatic Image Fusion of Real-Time Ultrasound and MR/CT Images for Radiofrequency Ablation of Hepatic Malignancies

2017 ◽  
Vol 43 ◽  
pp. S162
Author(s):  
Moon Hyung Choi ◽  
Joon Il Choi ◽  
Young Joon Lee ◽  
Sung Eun Rha ◽  
Jae Young Byun
Keyword(s):  
Radiofrequency Ablation ◽  
Image Fusion ◽  
Real Time ◽  
Ct Images ◽  
Hepatic Malignancies

Real-Time Image Fusion for Estimating the Therapeutic Effects of Radiofrequency Ablation on Hepatocellular Carcinoma

2017 ◽  
Vol 152 (5) ◽  
pp. S1173
Author(s):  
Nobuyuki Toshikuni ◽  
Yasuhiro Matsue ◽  
Kazuaki Ozaki ◽  
Nobuhiko Hayashi ◽  
Mutsumi Tsuchishima ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Radiofrequency Ablation ◽  
Image Fusion ◽  
Real Time ◽  
Therapeutic Effects ◽  
Real Time Image ◽  
Time Image

scholarly journals Software-based planning of ultrasound and CT-guided percutaneous radiofrequency ablation in hepatic tumors

2021 ◽  
Author(s):  
M. J. van Amerongen ◽  
P. Mariappan ◽  
P. Voglreiter ◽  
R. Flanagan ◽  
S. F. M. Jenniskens ◽  
...  
Keyword(s):  
Radiofrequency Ablation ◽  
Local Recurrence ◽  
Real Time ◽  
Sensitivity And Specificity ◽  
Gold Standard ◽  
Pearson Correlation ◽  
Visual Assessment ◽  
Simulation Software ◽  
Hepatic Tumors ◽  
Recurrence Rates

Abstract Objectives Radiofrequency ablation (RFA) can be associated with local recurrences in the treatment of liver tumors. Data obtained at our center for an earlier multinational multicenter trial regarding an in-house developed simulation software were re-evaluated in order to analyze whether the software was able to predict local recurrences. Methods Twenty-seven RFA ablations for either primary or secondary hepatic tumors were included. Colorectal liver metastases were shown in 14 patients and hepatocellular carcinoma in 13 patients. Overlap of the simulated volume and the tumor volume was automatically generated and defined as positive predictive value (PPV) and additionally visually assessed. Local recurrence during follow-up was defined as gold standard. Sensitivity and specificity were calculated using the visual assessment and gold standard. Results Mean tumor size was 18 mm (95% CI 15–21 mm). Local recurrence occurred in 5 patients. The PPV of the simulation showed a mean of 0.89 (0.84–0.93 95% CI). After visual assessment, 9 incomplete ablations were observed, of which 4 true positives and 5 false positives for the detection of an incomplete ablation. The sensitivity and specificity were, respectively, 80% and 77% with a correct prediction in 78% of cases. No significant correlation was found between size of the tumor and PPV (Pearson Correlation 0.10; p = 0.62) or between PPV and recurrence rates (Pearson Correlation 0.28; p = 0.16). Conclusions The simulation software shows promise in estimating the completeness of liver RFA treatment and predicting local recurrence rates, but could not be performed real-time. Future improvements in the field of registration could improve results and provide a possibility for real-time implementation.

Automatic image fusion of real-time ultrasound with computed tomography images: a prospective comparison between two auto-registration methods

2017 ◽  
Vol 58 (11) ◽  
pp. 1349-1357 ◽  
Author(s):  
Dong Ik Cha ◽  
Min Woo Lee ◽  
Ah Yeong Kim ◽  
Tae Wook Kang ◽  
Young-Taek Oh ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Fusion ◽  
Real Time ◽  
Ct Images ◽  
Rank Test ◽  
Initial Image ◽  
Major Drawback ◽  
Registration Error ◽  
Computed Tomography Images ◽  
Prospective Comparison

Background A major drawback of conventional manual image fusion is that the process may be complex, especially for less-experienced operators. Recently, two automatic image fusion techniques called Positioning and Sweeping auto-registration have been developed. Purpose To compare the accuracy and required time for image fusion of real-time ultrasonography (US) and computed tomography (CT) images between Positioning and Sweeping auto-registration. Material and Methods Eighteen consecutive patients referred for planning US for radiofrequency ablation or biopsy for focal hepatic lesions were enrolled. Image fusion using both auto-registration methods was performed for each patient. Registration error, time required for image fusion, and number of point locks used were compared using the Wilcoxon signed rank test. Results Image fusion was successful in all patients. Positioning auto-registration was significantly faster than Sweeping auto-registration for both initial (median, 11 s [range, 3–16 s] vs. 32 s [range, 21–38 s]; P < 0.001] and complete (median, 34.0 s [range, 26–66 s] vs. 47.5 s [range, 32–90]; P = 0.001] image fusion. Registration error of Positioning auto-registration was significantly higher for initial image fusion (median, 38.8 mm [range, 16.0–84.6 mm] vs. 18.2 mm [6.7–73.4 mm]; P = 0.029), but not for complete image fusion (median, 4.75 mm [range, 1.7–9.9 mm] vs. 5.8 mm [range, 2.0–13.0 mm]; P = 0.338]. Number of point locks required to refine the initially fused images was significantly higher with Positioning auto-registration (median, 2 [range, 2–3] vs. 1 [range, 1–2]; P = 0.012]. Conclusion Positioning auto-registration offers faster image fusion between real-time US and pre-procedural CT images than Sweeping auto-registration. The final registration error is similar between the two methods.

Fast registration of pre- and peri-interventional CT images for targeting support in radiofrequency ablation of hepatic tumors

2009 ◽  
Author(s):  
J. Bieberstein ◽  
C. Schumann ◽  
A. Weihusen ◽  
T. Boehler ◽  
S. Wirtz ◽  
...  
Keyword(s):  
Radiofrequency Ablation ◽  
Ct Images ◽  
Hepatic Tumors ◽  
Interventional Ct
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