Share:
Share this content in WeChat
X
Review
Research progress in MRI evaluation of the therapeutic effect of ablation in hepatocellular carcinoma
PANG Yaxuan  YIN Liang  ZHANG Jing  ZHAI Yanan  WANG Yinzhong  GUO Shunlin 

Cite this article as: PANG Y X, YIN L, ZHANG J, et al. Research progress in MRI evaluation of the therapeutic effect of ablation in hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(10): 200-204. DOI:10.12015/issn.1674-8034.2024.10.034.


[Abstract] Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide, ranks fourth among malignant tumors in China. Ablation therapy has been widely used for HCC, with advantages such as minimal impact on liver function, low trauma, and few complications. Accurately assessing post-ablation tumor survival, local recurrence, and metastasis is crucial for subsequent treatment. MRI is an important imaging modality for evaluating the efficacy of ablation in HCC. In recent years, research on Artificial intelligence (AI) in the field of liver cancer MRI has been increasing, demonstrating significant potential in predicting outcomes of ablation therapy. The integration of multimodal data using AI, such as combining genetic data with imaging data, is one of the key breakthroughs for future research. This paper comprehensively reviews the research progress of multimodal MRI and MRI-based AI in evaluating HCC ablation therapy, aiming to accurately assess residual tumors and predict early recurrence, providing a reference basis for individualized HCC treatment.
[Keywords] hepatocellular carcinoma;radiofrequency ablation;magnetic resonance imaging;artificial intelligence;efficacy evaluation

PANG Yaxuan   YIN Liang*   ZHANG Jing   ZHAI Yanan   WANG Yinzhong   GUO Shunlin  

Department of Radiology, the First Hospital of Lanzhou University, the First Clinical Medical College of Lanzhou University

Corresponding author: YIN L, E-mail: yinliang_ldyy@163.com

Conflicts of interest   None.

Received  2024-06-27
Accepted  2024-10-10
DOI: 10.12015/issn.1674-8034.2024.10.034
Cite this article as: PANG Y X, YIN L, ZHANG J, et al. Research progress in MRI evaluation of the therapeutic effect of ablation in hepatocellular carcinoma[J]. Chin J Magn Reson Imaging, 2024, 15(10): 200-204. DOI:10.12015/issn.1674-8034.2024.10.034.

[1]
LLOVET J M, KELLEY R K, VILLANUEVA A, et al. Hepatocellular carcinoma[J/OL]. Nat Rev Dis Primers, 2021, 7: 6 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/33479224/. DOI: 10.1038/s41572-020-00240-3.
[2]
Medical Administration Bureau of the National Health Commission. Standardization for diagnosis and treatment of hepatocellular carcinoma(2022 edition)[J]. Chin J Pract Surg, 2022, 42(3): 241-273. DOI: 10.19538/j.cjps.issn1005-2208.2022.03.01.
[3]
REIG M, FORNER A, RIMOLA J, et al. BCLC strategy for prognosis prediction and treatment recommendation: the 2022 update[J]. J Hepatol, 2022, 76(3): 681-693. DOI: 10.1016/j.jhep.2021.11.018.
[4]
CROCETTI L, SCALISE P, BOZZI E, et al. Thermal ablation of hepatocellular carcinoma[J]. J Med Imaging Radiat Oncol, 2023, 67(8): 817-831. DOI: 10.1111/1754-9485.13613.
[5]
WANG D D, LI X G. Research status and progress on tumor residue after hepatocellular carcinoma radiofrequency ablation[J]. Interv Radiol, 2019, 28(08): 800-804. DOI: 10.3969/j.issn.1008-794X.2019.08.021.
[6]
ZHANG L K, DU F, ZHANG Y X, et al. Microwave ablation is superior to radiofrequency ablation in the treatment of hepatocellular carcinoma below 5 cm - A systematic review and meta-analysis[J]. J Minim Access Surg, 2023, 19(4): 453-458. DOI: 10.4103/jmas.jmas_344_22.
[7]
SHIMIZU R, IDA Y, KITANO M. Predicting outcome after percutaneous ablation for early-stage hepatocellular carcinoma using various imaging modalities[J/OL]. Diagnostics, 2023, 13(19): 3058 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/37835800/. DOI: 10.3390/diagnostics13193058.
[8]
ZHANG Y, WEI H, SONG B. Magnetic resonance imaging for treatment response evaluation and prognostication of hepatocellular carcinoma after thermal ablation[J/OL]. Insights Imaging, 2023, 14(1): 87 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/37188987/. DOI: 10.1186/s13244-023-01440-7.
[9]
BRANCATO V, CERRONE M, GARBINO N, et al. Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: a quantitative review with Radiomics Quality Score[J]. World J Gastroenterol, 2024, 30(4): 381-417. DOI: 10.3748/wjg.v30.i4.381.
[10]
YANG X Z, YUAN C W, ZHANG Y H, et al. Predicting hepatocellular carcinoma early recurrence after ablation based on magnetic resonance imaging radiomics nomogram[J/OL]. Medicine, 2022, 101(52): e32584 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/36596081/. DOI: 10.1097/MD.0000000000032584.
[11]
BO Z Y, SONG J T, HE Q K, et al. Application of artificial intelligence radiomics in the diagnosis, treatment, and prognosis of hepatocellular carcinoma[J/OL]. Comput Biol Med, 2024, 173: 108337 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/38547656/. DOI: 10.1016/j.compbiomed.2024.108337.
[12]
ZWANENBURG A, VALLIÈRES M, ABDALAH M A, et al. The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping[J]. Radiology, 2020, 295(2): 328-338. DOI: 10.1148/radiol.2020191145.
[13]
VOIZARD N, CERNY M, ASSAD A, et al. Assessment of hepatocellular carcinoma treatment response with LI-RADS: A pictorial review[J/OL]. Insights Imaging, 2019, 10(1): 121 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/31853668/. DOI: 10.1186/s13244-019-0801-z.
[14]
GRANATA V, GRASSI R, FUSCO R, et al. Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma[J/OL]. Infect Agent Cancer, 2021, 16(1): 53 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/34281580/. DOI: 10.1186/s13027-021-00393-0.
[15]
HU C G, SONG Y D, ZHANG J, et al. Preoperative gadoxetic acid-enhanced MRI based nomogram improves prediction of early HCC recurrence after ablation therapy[J/OL]. Front Oncol, 2021, 11: 649682 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/34094938/. DOI: 10.3389/fonc.2021.649682.
[16]
MAHMOUD B E M H, ELKHOLY S F, NABEEL M M, et al. Role of MRI in the assessment of treatment response after radiofrequency and microwave ablation therapy for hepatocellular carcinoma[J]. Egypt J Radiol Nucl Med, 2016, 47(2): 377-385. DOI: 10.1016/j.ejrnm.2016.01.007.
[17]
MAINO C, VERNUCCIO F, CANNELLA R, et al. Non-invasive imaging biomarkers in chronic liver disease[J/OL]. Eur J Radiol, 2024, 181: 111749 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/39317002/. DOI: 10.1016/j.ejrad.2024.111749.
[18]
BARAT M, FOHLEN A, CASSINOTTO C, et al. One-month apparent diffusion coefficient correlates with response to radiofrequency ablation of hepatocellular carcinoma[J]. J Magn Reson Imaging, 2017, 45(6): 1648-1658. DOI: 10.1002/jmri.25521.
[19]
MA X H, OUYANG H, WANG S, et al. Histogram analysis of apparent diffusion coefficient predicts response to radiofrequency ablation in hepatocellular carcinoma[J]. Chin J Cancer Res, 2019, 31(2): 366-374. DOI: 10.21147/j.issn.1000-9604.2019.02.11.
[20]
ZHANG Z H, YU J, LIU S S, et al. Multiparametric liver MRI for predicting early recurrence of hepatocellular carcinoma after microwave ablation[J/OL]. Cancer Imaging, 2022, 22(1): 42 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/36042507/. DOI: 10.1186/s40644-022-00471-5.
[21]
TAO Y Y, ZHOU Y, WANG R, et al. Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases[J]. World J Clin Cases, 2020, 8(15): 3164-3176. DOI: 10.12998/wjcc.v8.i15.3164.
[22]
HUSSEIN R S, TANTAWY W, ABBAS Y A. MRI assessment of hepatocellular carcinoma after locoregional therapy[J/OL]. Insights Imaging, 2019, 10(1): 8 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/30694398/. DOI: 10.1186/s13244-019-0690-1.
[23]
GUO Z Y, ZHANG Q, LI X G, et al. Intravoxel incoherent motion diffusion weighted MR imaging for monitoring the instantly therapeutic efficacy of radiofrequency ablation in rabbit VX2 tumors without evident links between conventional perfusion weighted images[J/OL]. PLoS One, 2015, 10(5): e0127964 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/26020785/. DOI: 10.1371/journal.pone.0127964.
[24]
LIAN S S, SHI F, WEI K K, et al. Intravoxel incoherent motion diffusion-weighted MR imaging for early evaluation of the effect of radiofrequency ablation in rabbit liver VX2 tumors[J]. Acad Radiol, 2018, 25(9): 1128-1135. DOI: 10.1016/j.acra.2018.01.010.
[25]
CAO X, SHI H, DOU W Q, et al. Can DKI-MRI predict recurrence and invasion of peritumoral zone of hepatocellular carcinoma after transcatheter arterial chemoembolization?[J]. World J Gastrointest Surg, 2022, 14(10): 1150-1160. DOI: 10.4240/wjgs.v14.i10.1150.
[26]
YUAN Z G, WANG Z Y, XIA M Y, et al. Comparison of diffusion kurtosis imaging versus diffusion weighted imaging in predicting the recurrence of early stage single nodules of hepatocellular carcinoma treated by radiofrequency ablation[J/OL]. Cancer Imaging, 2019, 19(1): 30 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/31142356/. DOI: 10.1186/s40644-019-0213-9.
[27]
YUAN Z G, WANG Z Y, XIA M Y, et al. Diffusion kurtosis imaging for assessing the therapeutic response of transcatheter arterial chemoembolization in hepatocellular carcinoma[J]. J Cancer, 2020, 11(8): 2339-2347. DOI: 10.7150/jca.32491.
[28]
ZHONG L H, LIU W G, LI W Z. Advances in the application of magnetic resonance elastography in the diagnosis and treatment of hepatocellular carcinoma[J]. Chin J Magn Reson Imag, 2022, 13(12): 150-153, 158. DOI: 10.12015/issn.1674-8034.2022.12.028.
[29]
CHO H J, KIM B, KIM H J, et al. Liver stiffness measured by MR elastography is a predictor of early HCC recurrence after treatment[J]. Eur Radiol, 2020, 30(8): 4182-4192. DOI: 10.1007/s00330-020-06792-y.
[30]
VOGL T J, DOSCH M P, HAAS Y. MR elastography is a good response parameter for microwave ablation liver tumors[J/OL]. Eur J Radiol, 2022, 152: 110360 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/35597071/. DOI: 10.1016/j.ejrad.2022.110360.
[31]
CASTERA L, FRIEDRICH-RUST M, LOOMBA R. Noninvasive assessment of liver disease in patients with nonalcoholic fatty liver disease[J]. Gastroenterology, 2019, 156(5): 1264-1281. DOI: 10.1053/j.gastro.2018.12.036.
[32]
IMAI Y, KATAYAMA K, HORI M, et al. Prospective comparison of Gd-EOB-DTPA-enhanced MRI with dynamic CT for detecting recurrence of HCC after radiofrequency ablation[J]. Liver Cancer, 2017, 6(4): 349-359. DOI: 10.1159/000481416.
[33]
BAE J S, KIM J H, LEE D H, et al. Hepatobiliary phase of gadoxetic acid-enhanced MRI in patients with HCC: prognostic features before resection, ablation, or TACE[J]. Eur Radiol, 2021, 31(6): 3627-3637. DOI: 10.1007/s00330-020-07499-w.
[34]
ÖCAL O, SCHÜTTE K, MALFERTHEINER P, et al. Prognostic value of baseline MRI features in patients treated with thermal ablation for hepatocellular carcinoma[J/OL]. Eur J Radiol, 2023, 168: 111120 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/37806190/. DOI: 10.1016/j.ejrad.2023.111120.
[35]
WANG R Z, XU H T, CHEN W F, et al. Gadoxetic acid-enhanced MRI with a focus on LI-RADS v2018 imaging features predicts the prognosis after radiofrequency ablation in small hepatocellular carcinoma[J/OL]. Front Oncol, 2023, 13: 975216 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/36816925/. DOI: 10.3389/fonc.2023.975216.
[36]
KIM T H, WOO S, HAN S, et al. Hepatobiliary phase hypointense nodule without arterial phase hyperenhancement: are they at risk of HCC recurrence after ablation or surgery? A systematic review and meta-analysis[J]. Eur Radiol, 2020, 30(3): 1624-1633. DOI: 10.1007/s00330-019-06499-9.
[37]
RIMOLA J, DAVENPORT M S, LIU P S, et al. Diagnostic accuracy of MRI with extracellular vs. hepatobiliary contrast material for detection of residual hepatocellular carcinoma after locoregional treatment[J]. Abdom Radiol, 2019, 44(2): 549-558. DOI: 10.1007/s00261-018-1775-x.
[38]
CHERNYAK V, FOWLER K J, HEIKEN J P, et al. Use of gadoxetate disodium in patients with chronic liver disease and its implications for liver imaging reporting and data system (LI-RADS)[J]. J Magn Reson Imaging, 2019, 49(5): 1236-1252. DOI: 10.1002/jmri.26540.
[39]
LIU S S, WU J P, DING W Z, et al. The tumor ghost on MRI after microwave ablation for hepatocellular carcinoma: A new modality to assess the ablative margin[J/OL]. Eur J Radiol, 2023, 158: 110617 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/36463706/. DOI: 10.1016/j.ejrad.2022.110617.
[40]
JIANG C, CAI Y Q, YANG J J, et al. Radiomics in the diagnosis and treatment of hepatocellular carcinoma[J]. Hepatobiliary Pancreat Dis Int, 2023, 22(4): 346-351. DOI: 10.1016/j.hbpd.2023.03.010.
[41]
WEN L T, WENG S P, YAN C, et al. A radiomics nomogram for preoperative prediction of early recurrence of small hepatocellular carcinoma after surgical resection or radiofrequency ablation[J/OL]. Front Oncol, 2021, 11: 657039 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/34026632/. DOI: 10.3389/fonc.2021.657039.
[42]
PENG W, JIANG X H, ZHANG W D, et al. A radiomics-based model can predict recurrence-free survival of hepatocellular carcinoma after curative ablation[J]. Asian J Surg, 2023, 46(7): 2689-2696. DOI: 10.1016/j.asjsur.2022.09.130.
[43]
ISEKE S, ZEEVI T, KUCUKKAYA A S, et al. Machine learning models for prediction of posttreatment recurrence in early-stage hepatocellular carcinoma using pretreatment clinical and MRI features: a proof-of-concept study[J]. AJR Am J Roentgenol, 2023, 220(2): 245-255. DOI: 10.2214/AJR.22.28077.
[44]
HU H T, SHAN Q Y, CHEN S L, et al. CT-based radiomics for preoperative prediction of early recurrent hepatocellular carcinoma: technical reproducibility of acquisition and scanners[J]. Radiol Med, 2020, 125(8): 697-705. DOI: 10.1007/s11547-020-01174-2.
[45]
AN C, JIANG Y Q, HUANG Z M, et al. Assessment of ablative margin after microwave ablation for hepatocellular carcinoma using deep learning-based deformable image registration[J/OL]. Front Oncol, 2020, 10: 573316 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/33102233/. DOI: 10.3389/fonc.2020.573316.
[46]
CHEN C, HAN Q Y, REN H, et al. Multiparametric MRI-based model for prediction of local progression of hepatocellular carcinoma after thermal ablation[J]. Cancer Med, 2023, 12(17): 17529-17540. DOI: 10.1002/cam4.6277.
[47]
WANG W T, WANG Y Y, SONG D J, et al. A Transformer-Based microvascular invasion classifier enhances prognostic stratification in HCC following radiofrequency ablation[J]. Liver Int, 2024, 44(4): 894-906. DOI: 10.1111/liv.15846.
[48]
BIONDETTI P, ASCENTI V, SHEHAB A, et al. Percutaneous microwave ablation of hepatocellular carcinoma with "double fusion" technique: technical note and single-center preliminary experience[J/OL]. Diagnostics, 2023, 13(14): 2349 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/37510092/. DOI: 10.3390/diagnostics13142349.
[49]
TAO J, FENG G Y, TANG G, et al. Efficacy and safety of fusion imaging in radiofrequency ablation of hepatocellular carcinoma compared to ultrasound: A meta-analysis[J/OL]. Front Surg, 2021, 8: 728098 [2024-06-26]. https://pubmed.ncbi.nlm.nih.gov/34938766/. DOI: 10.3389/fsurg.2021.728098.
[50]
WANG F Q, NUMATA K, NIHONMATSU H, et al. Intraprocedurally EOB-MRI/US fusion imaging focusing on hepatobiliary phase findings can help to reduce the recurrence of hepatocellular carcinoma after radiofrequency ablation[J]. Int J Hyperthermia, 2020, 37(1): 1149-1158. DOI: 10.1080/02656736.2020.1825837.
[51]
KOBE A, KINDLER Y, KLOTZ E, et al. Fusion of preinterventional MR imaging with liver perfusion CT after RFA of hepatocellular carcinoma: early quantitative prediction of local recurrence[J]. Invest Radiol, 2021, 56(3): 188-196. DOI: 10.1097/RLI.0000000000000726.
[52]
YOON J H, LEE J M, KLOTZ E, et al. Prediction of local tumor progression after radiofrequency ablation (RFA) of hepatocellular carcinoma by assessment of ablative margin using pre-RFA MRI and post-RFA CT registration[J]. Korean J Radiol, 2018, 19(6): 1053-1065. DOI: 10.3348/kjr.2018.19.6.1053.
[53]
TAKEYAMA N, MIZOBUCHI N, SAKAKI M, et al. Evaluation of hepatocellular carcinoma ablative margins using fused pre- and post-ablation hepatobiliary phase images[J]. Abdom Radiol, 2019, 44(3): 923-935. DOI: 10.1007/s00261-018-1800-0.
[54]
SHENG Y G, SUN X K, SUN H M, et al. Fusion imaging versus ultrasound-guided percutaneous thermal ablation of liver cancer: a meta-analysis[J]. Acta Radiol, 2023, 64(9): 2506-2517. DOI: 10.1177/02841851231187638.
[55]
LIU Z Y, LU C. Application of artificial intelligence in imaging for tumor diagnosis and treatment[J]. Int J Med Radiol, 2024, 47(3): 257-259. DOI: 10.19300/j.2024.S21528.

PREV Advances in 4D Flow CMR quantitative analysis of intracardiac hemodynamics
NEXT MRI-Based Artificial Intelligence in Lymph Node Metastasis of Rectal Cancer
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn