Habitat imaging’s role in predicting HCC percentage in combined hepatocellular carcinoma-cholangiocarcinoma and its biologic underpinnings

Motivation: The prognostic value of component percentage in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) was verified, but the identification of percentage of each component relies on extensive tumor sampling. Goal(s): Therefore, the aim of this study was to investigate if MRI-based habitat imaging helps to predict component percentage in cHCC-CCA preoperatively,Approach: and to further verify the biologic underpinnings of habitat imaging in cHCC-CCA by analyzing RNA sequencing data. Results: We found that preoperative prediction of HCC percentage in patients with cHCC-CCA can be achieved using an MRI-based habitat imaging model, which was also associated with signaling pathways regulating cell migration and tumor metastasis. Impact: We achieved prediction of HCC percentage through an MRI-based habitat imaging model, and revealed the biologic underpinnings of habitat imaging, that is, habitat imaging may identify patients at risk of metastasis. These results may guide individual management in cHCC-CCA patients.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/4135
Primary Topic
Cholangiocarcinoma and Gallbladder Cancer Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Habitat imaging’s role in predicting HCC percentage in combined hepatocellular carcinoma-cholangiocarcinoma and its biologic underpinnings

Mengsu Zeng, C. Y. Yang, Yuyao Xiao, Yunfei Zhang
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Cholangiocarcinoma and Gallbladder Cancer Studies
article

Habitat imaging’s role in predicting HCC percentage in combined hepatocellular carcinoma-cholangiocarcinoma and its biologic underpinnings

Mengsu Zeng, C. Y. Yang, Yuyao Xiao, Yunfei Zhang
article en

Abstract

Motivation: The prognostic value of component percentage in combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) was verified, but the identification of percentage of each component relies on extensive tumor sampling. Goal(s): Therefore, the aim of this study was to investigate if MRI-based habitat imaging helps to predict component percentage in cHCC-CCA preoperatively,Approach: and to further verify the biologic underpinnings of habitat imaging in cHCC-CCA by analyzing RNA sequencing data. Results: We found that preoperative prediction of HCC percentage in patients with cHCC-CCA can be achieved using an MRI-based habitat imaging model, which was also associated with signaling pathways regulating cell migration and tumor metastasis. Impact: We achieved prediction of HCC percentage through an MRI-based habitat imaging model, and revealed the biologic underpinnings of habitat imaging, that is, habitat imaging may identify patients at risk of metastasis. These results may guide individual management in cHCC-CCA patients.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Life in Land
Openalex Percentile: Top 60%
Cholangiocarcinoma and Gallbladder Cancer Studies
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Habitat imaging’s role in predicting HCC percentage in combined hepatocellular carcinoma-cholangiocarcinoma and its biologic underpinnings — Mengsu Zeng, C. Y. Yang, et al. · Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024) | TGRS Research Map | TGRS