Enhanced necrosis visualization in liver ablation monitoring with fiber artifact removal: a cadaver study

Surgical resection is a common treatment for liver cancers. When tumors are unresectable, minimally invasive percutaneous radiofrequency ablation (RFA) is an alternative treatment option. Yet, due to challenges in monitoring ablation boundaries, RFA treatment often has a higher recurrence rate. Medical ultrasound (US) imaging is a frequently used tool to oversee various surgical and interventional procedures. However, US imaging has insufficient contrast to visualize ablation-induced necrosis in RFA procedures. This study explores the use of spectroscopic photoacoustic (sPA) imaging techniques leveraging a customized diffusing fiber to enhance the visualization of ablation-induced lesions. While the diffusing fiber enables wide-area illumination, artifacts caused by nonuniform illumination originating from sidelobe interference pose a challenge. Therefore, we implemented the standard Hough Transform (SHT) method to suppress these artifacts, improving the accuracy of necrotic mapping. Using a swine cadaver model, the sPA imaging system demonstrated its capability to identify ablation-induced necrosis, with results confirmed by gross pathology. The detected ablation-induced lesion was measured at 7.81 mm by 6.31 mm in PA imaging, closely aligning with the 7.93 mm average diameter based on pathology. These findings indicate that our approach effectively suppresses artifacts and accurately identifies ablated regions underneath the skin surface. This study concludes that PA-guided ablation could be a viable tool in clinical practice to improve the precision and hence patient outcome of liver RFA procedures.

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Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1117/12.3048797
Primary Topic
Cardiovascular Function and Risk Factors
Type
article
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article

Enhanced necrosis visualization in liver ablation monitoring with fiber artifact removal: a cadaver study

Oliver Jonas, Yinghui Hua, Sharath K. Bhagavatula, Guigen Liu et al.
Cardiovascular Function and Risk Factors
article

Enhanced necrosis visualization in liver ablation monitoring with fiber artifact removal: a cadaver study

Oliver Jonas, Yinghui Hua, Sharath K. Bhagavatula, Guigen Liu, Xihan Ma, Shang Gao, Haichong K. Zhang
article en

Abstract

Surgical resection is a common treatment for liver cancers. When tumors are unresectable, minimally invasive percutaneous radiofrequency ablation (RFA) is an alternative treatment option. Yet, due to challenges in monitoring ablation boundaries, RFA treatment often has a higher recurrence rate. Medical ultrasound (US) imaging is a frequently used tool to oversee various surgical and interventional procedures. However, US imaging has insufficient contrast to visualize ablation-induced necrosis in RFA procedures. This study explores the use of spectroscopic photoacoustic (sPA) imaging techniques leveraging a customized diffusing fiber to enhance the visualization of ablation-induced lesions. While the diffusing fiber enables wide-area illumination, artifacts caused by nonuniform illumination originating from sidelobe interference pose a challenge. Therefore, we implemented the standard Hough Transform (SHT) method to suppress these artifacts, improving the accuracy of necrotic mapping. Using a swine cadaver model, the sPA imaging system demonstrated its capability to identify ablation-induced necrosis, with results confirmed by gross pathology. The detected ablation-induced lesion was measured at 7.81 mm by 6.31 mm in PA imaging, closely aligning with the 7.93 mm average diameter based on pathology. These findings indicate that our approach effectively suppresses artifacts and accurately identifies ablated regions underneath the skin surface. This study concludes that PA-guided ablation could be a viable tool in clinical practice to improve the precision and hence patient outcome of liver RFA procedures.

Worcester Polytechnic Institute (US), Harvard University (US), Harvard University Press (US)
Zero hunger
Openalex Percentile: Top 88%
Cardiovascular Function and Risk Factors
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