The AI Prognostic Assessment and Pathological Basis Research of Early HCC After Minimally Invasive Treatment

Hepatocellular Carcinoma Clinical Trial

Official title:

The Artificial Intelligent Prognostic Assessment and Pathological Basis Research of Early Primary Hepatocellular Carcinoma After Minimally Invasive Treatment Based on Multimodal MRI and Clinical Big Data

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT04299919
• Other study ID #: PJ-KS-KY-2019-167
• Status: Active, not recruiting
• Start date: April 1, 2007
• Est. completion date: June 30, 2024

Study information

• Verified date: March 2020
• Source: The First Affiliated Hospital of Dalian Medical University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The study evaluates artificial intelligence method based on multimodal magnetic resonance imaging (MRI) images and clinical data in preoperative prediction of prognosis in early hepatocellular carcinoma (HCC) patients treated with minimally invasive treatment. The correlation between prognosis-related MRI features and pathological features was studied through artificial intelligence method, so as to provide the interpretability of image features for predicting the prognosis of HCC patients treated with minimally invasive treatment.

Description:

The prognosis prediction of early stage hepatocellular carcinoma (HCC) after minimally invasive treatment involves clinical decision of treatment and follow-up. Magnetic resonance imaging (MRI) has become the main approach for monitoring and following up of HCC, however it's difficult to predict HCC prognosis before surgery. We found the following limitations among previous researches: multimodal MRI using different sequences shows uncertain boundaries of HCC, which makes precise segmentation more difficult, and also leads to an additional workload for extracting high throughput radiomics features, which are limited in quantity and repeatability. Regarding to prognosis aspect, the MRI images, clinical data, and follow up information have not been fully exploited yet. In addition, the prognosis result obtained by radiomics workflow is difficult to be explained and applied to clinical application. Therefore, we conduct a study to solve the problems mentioned above: (1) To explore an effective deep learning neural network method and a pre-training model for improving tumor segmentation accuracy. (2) To establish a method for extracting high-throughput multi-dimensional and multimodal MRI radiomics features related to HCC prognosis. (3) To explore a correlation between "multimodal MRI based pathological features of early stage HCC" and the results of "multimodal MRI based prognosis depth network of early stage HCC after minimally invasive treatment". Based on above approaches, we aim to establish "multimodal MRI based prognosis model of early stage HCC after minimally invasive treatment" in different clinical application scenarios guiding to clinical decision-making. Moreover, we also aim to explore the correlation between MRI radiomics features and pathology, which provides theoretical foundations for the MRI radiomics based pathological researches.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 1200
• Est. completion date: June 30, 2024
• Est. primary completion date: June 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Hepatocellular carcinoma patients received minimally invasive treatment (transcatheter arterial chemoembolization, radiofrequency ablation, or combined) or hepatectomy;

• Patients received MRI examination within 1 month before treatment;

• Complete post-treatment prognosis information.

Exclusion Criteria:

• local or systemic treatment before MR examination;

• Incomplete clinical and pathological data;

• Heavy image artifacts.

Related Conditions & MeSH terms

• Carcinoma
• Carcinoma, Hepatocellular
• Hepatocellular Carcinoma

Intervention

Procedure:
• Minimally invasive treatment
All hepatocellular carcinoma (HCC) patients received minimally invasive treatment, including transcatheter arterial chemoembolization (TACE), radiofrequency ablation (RFA) or combined.
• Hepatectomy
All hepatocellular carcinoma (HCC) patients received hepatectomy.

Locations

Country	Name	City	State
China	The First Affiliated Hospital of Dalian Medical University	Dalian	Liaoning

Sponsors (1)

Lead Sponsor	Collaborator
The First Affiliated Hospital of Dalian Medical University

Country where clinical trial is conducted

China, 

References & Publications (21)

Bloomston M, Binitie O, Fraiji E, Murr M, Zervos E, Goldin S, Kudryk B, Zwiebel B, Black T, Fargher S, Rosemurgy AS. Transcatheter arterial chemoembolization with or without radiofrequency ablation in the management of patients with advanced hepatic malignancy. Am Surg. 2002 Sep;68(9):827-31. — View Citation

Choi JW, Chung JW, Lee DH, Kim HC, Hur S, Lee M, Jae HJ. Portal hypertension is associated with poor outcome of transarterial chemoembolization in patients with hepatocellular carcinoma. Eur Radiol. 2018 May;28(5):2184-2193. doi: 10.1007/s00330-017-5145-9. Epub 2017 Dec 7. — View Citation

Hasdemir DB, Dávila LA, Schweitzer N, Meyer BC, Koch A, Vogel A, Wacker F, Rodt T. Evaluation of CT vascularization patterns for survival prognosis in patients with hepatocellular carcinoma treated by conventional TACE. Diagn Interv Radiol. 2017 May-Jun;23(3):217-222. doi: 10.5152/dir.2016.16006. — View Citation

Huang YL, Chen JH, Shen WC. Diagnosis of hepatic tumors with texture analysis in nonenhanced computed tomography images. Acad Radiol. 2006 Jun;13(6):713-20. — View Citation

Hui TCH, Chuah TK, Low HM, Tan CH. Predicting early recurrence of hepatocellular carcinoma with texture analysis of preoperative MRI: a radiomics study. Clin Radiol. 2018 Dec;73(12):1056.e11-1056.e16. doi: 10.1016/j.crad.2018.07.109. Epub 2018 Sep 10. — View Citation

Ibragimov B, Toesca D, Chang D, Koong A, Xing L. Combining deep learning with anatomical analysis for segmentation of the portal vein for liver SBRT planning. Phys Med Biol. 2017 Nov 10;62(23):8943-8958. doi: 10.1088/1361-6560/aa9262. — View Citation

Kim J, Choi SJ, Lee SH, Lee HY, Park H. Predicting Survival Using Pretreatment CT for Patients With Hepatocellular Carcinoma Treated With Transarterial Chemoembolization: Comparison of Models Using Radiomics. AJR Am J Roentgenol. 2018 Nov;211(5):1026-1034. doi: 10.2214/AJR.18.19507. Epub 2018 Sep 21. — View Citation

Kim NH, Lee T, Cho YK, Kim BI, Kim HJ. Impact of clinically evident portal hypertension on clinical outcome of patients with hepatocellular carcinoma treated by transarterial chemoembolization. J Gastroenterol Hepatol. 2018 Jul;33(7):1397-1406. doi: 10.1111/jgh.14083. Epub 2018 Mar 12. — View Citation

Lam A, Fernando D, Sirlin CC, Nayyar M, Goodwin SC, Imagawa DK, Lall C. Value of the portal venous phase in evaluation of treated hepatocellular carcinoma following transcatheter arterial chemoembolisation. Clin Radiol. 2017 Nov;72(11):994.e9-994.e16. doi: 10.1016/j.crad.2017.07.003. Epub 2017 Aug 2. — View Citation

Li S, Zhang L, Huang ZM, Wu PH. Transcatheter arterial chemoembolization combined with CT-guided percutaneous thermal ablation versus hepatectomy in the treatment of hepatocellular carcinoma. Chin J Cancer. 2015 Jun 10;34(6):254-63. doi: 10.1186/s40880-015-0023-9. — View Citation

Li Z, Mao Y, Huang W, Li H, Zhu J, Li W, Li B. Texture-based classification of different single liver lesion based on SPAIR T2W MRI images. BMC Med Imaging. 2017 Jul 13;17(1):42. doi: 10.1186/s12880-017-0212-x. — View Citation

Pang Q, Zhang JY, Xu XS, Song SD, Chen W, Zhou YY, Miao RC, Qu K, Liu SS, Dong YF, Liu C. The prognostic values of 12 cirrhosis-relative noninvasive models in patients with hepatocellular carcinoma. Scand J Clin Lab Invest. 2015 Jan;75(1):73-84. doi: 10.3109/00365513.2014.981759. Epub 2014 Dec 3. — View Citation

Shao GL, Zheng JP, Guo LW, Chen YT, Zeng H, Yao Z. Evaluation of efficacy of transcatheter arterial chemoembolization combined with computed tomography-guided radiofrequency ablation for hepatocellular carcinoma using magnetic resonance diffusion weighted imaging and computed tomography perfusion imaging: A prospective study. Medicine (Baltimore). 2017 Jan;96(3):e5518. doi: 10.1097/MD.0000000000005518. — View Citation

Song W, Yu X, Guo D, Liu H, Tang Z, Liu X, Zhou J, Zhang H, Liu Y, Liu X. MRI-Based Radiomics: Associations With the Recurrence-Free Survival of Patients With Hepatocellular Carcinoma Treated With Conventional Transcatheter Arterial Chemoembolization. J Magn Reson Imaging. 2019 Nov 1. doi: 10.1002/jmri.26977. [Epub ahead of print] — View Citation

Tang H, Bai HX, Su C, Lee AM, Yang L. The effect of cirrhosis on radiogenomic biomarker's ability to predict microvascular invasion and outcome in hepatocellular carcinoma. Hepatology. 2016 Aug;64(2):691-2. doi: 10.1002/hep.28620. Epub 2016 May 31. — View Citation

Wang J, Shen JL. Spectral CT in evaluating the therapeutic effect of transarterial chemoembolization for hepatocellular carcinoma: A retrospective study. Medicine (Baltimore). 2017 Dec;96(52):e9236. doi: 10.1097/MD.0000000000009236. — View Citation

Wu LF, Rao SX, Xu PJ, Yang L, Chen CZ, Liu H, Huang JF, Fu CX, Halim A, Zeng MS. Pre-TACE kurtosis of ADC(total) derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma. Eur Radiol. 2019 Jan;29(1):213-223. doi: 10.1007/s00330-018-5482-3. Epub 2018 Jun 19. — View Citation

Wu M, Tan H, Gao F, Hai J, Ning P, Chen J, Zhu S, Wang M, Dou S, Shi D. Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Eur Radiol. 2019 Jun;29(6):2802-2811. doi: 10.1007/s00330-018-5787-2. Epub 2018 Nov 7. — View Citation

Yasaka K, Akai H, Abe O, Kiryu S. Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study. Radiology. 2018 Mar;286(3):887-896. doi: 10.1148/radiol.2017170706. Epub 2017 Oct 23. — View Citation

Ye JZ, Chen JZ, Li ZH, Bai T, Chen J, Zhu SL, Li LQ, Wu FX. Efficacy of postoperative adjuvant transcatheter arterial chemoembolization in hepatocellular carcinoma patients with microvascular invasion. World J Gastroenterol. 2017 Nov 7;23(41):7415-7424. doi: 10.3748/wjg.v23.i41.7415. — View Citation

Zhou Y, He L, Huang Y, Chen S, Wu P, Ye W, Liu Z, Liang C. CT-based radiomics signature: a potential biomarker for preoperative prediction of early recurrence in hepatocellular carcinoma. Abdom Radiol (NY). 2017 Jun;42(6):1695-1704. doi: 10.1007/s00261-017-1072-0. — View Citation

* Note: There are 21 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Three-month recurrence	All HCC patients have been regularly monitored for recurrence via contrast CT or MRI for at least three months.	Three months
Primary	Six-month recurrence	All HCC patients have been regularly monitored for recurrence via contrast CT or MRI for at least six months.	Six months
Primary	One-year recurrence	All HCC patients have been regularly monitored for recurrence via contrast CT or MRI for at least one year.	One year
Primary	Two-year recurrence	All HCC patients have been regularly monitored for recurrence via contrast CT or MRI for at least two years.	Two years
Primary	Three-year recurrence	All HCC patients have been regularly monitored for recurrence via contrast CT or MRI for at least three years.	Three years
Secondary	Progression-free survival	The time between the tumor progression and initial treatment was recorded.	Three months, six months, one year, two years, and three years.

External Links

•   A radiomics study.
•   Comparison of Models Using Radiomics.
•   CT-based radiomics signature.
•   Deep Learning.
•   Diagnosis of hepatic tumors with texture analysis.
•   Efficacy of postoperative in hepatocellular carcinoma patients with microvascular invasion.
•   Evaluation of the efficacy of hepatocellular carcinoma.
•   MRI-Based Radiomics.
•   Portal hypertension is associated with poor outcome of transarterial chemoembolization in patients with hepatocellular carcinoma.
•   Portal hypertension.
•   Predicting the grade of hepatocellular carcinoma.
•   Texture-based classification of different single liver lesion.
•   The best independent predictor of prognosis in hepatocellular carcinoma.
•   The predicting microvascular invasion and outcome in hepatocellular carcinoma.
•   The prognostic values.
•   The segmentation of the portal vein.
•   The survival prognosis in patients with hepatocellular carcinoma treated by conventional TACE.
•   The therapeutic effect of transarterial chemoembolization for hepatocellular carcinoma.
•   Transcatheter arterial chemoembolisation.
•   Transcatheter arterial chemoembolization.
•   Transcatheter arterial chemoembolization.