Share:
Share this content in WeChat
X
Clinical Article
Evaluation and prediction of therapeutic effect of hepatocellular carcinoma after TACE based on contrast enhanced MRI histogram analysis
WANG Dongdong  LI Xiaoming  YANG Liu  ZHANG Sijia 

Cite this article as: WANG D D, LI X M, YANG L, et al. Evaluation and prediction of therapeutic effect of hepatocellular carcinoma after TACE based on contrast enhanced MRI histogram analysis[J]. Chin J Magn Reson Imaging, 2024, 15(1): 113-118, 131. DOI:10.12015/issn.1674-8034.2024.01.018.


[Abstract] Objective To evaluate and predict the early curative effect of transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma based on contrast-enhanced magnetic resonance imaging (CE-MRI) histogram parameters of MRI.Materials and Methods Sixty-four patients with hepatocellular carcinoma confirmed by pathological biopsy or clinically diagnosed from June 2018 to December 2021 were selected for study. All patients underwent routine MR scan and multi-phase dynamic enhanced T1WI contrast-enhanced scan within 1 month before TACE treatment and 4-6 weeks after the first TACE treatment. According to the modified solid tumor efficacy evaluation criteria (mRECIST), the patients were divided into effective group of 34 cases and ineffective group of 30 cases. The HCC maximum axial T1WI images (arterial phase, portal phase and delayed phase) of HCC maximum slice images were selected for all patients, and the histogram features of the lesions were manually extracted by sketching ROI with MaZda software, including mean, variance, skewness, kurtosis and the values of the 1st, 10th, 50th, 90th and 99th percentiles (recorded as Perc1, Perc10, Pere50, Perc90 and Perc99, respectively). Statistical software was used to compare the differences of histogram parameters between effective group and ineffective group before and after TACE treatment. The parameters with statistical differences in the postoperative efficacy of HCC were evaluated by the receiver operating characteristic (ROC) curve, and the valuable parameter values and thresholds were obtained.Results The parameters with statistically significant differences between the two groups before TACE treatment including mean value, Perc50, Perc90, Perc99 in arterial phase, Perc1 in venous phase, and peak value in delayed phase (P<0.05); the parameters with statistically significant differences between the two groups after TACE treatment including the mean value of delay period, Perc50, Perc99 (P<0.05); there was no statistically significant difference in the other parameters between the two groups before and after TACE treatment (P>0.05). The ROC curve results showed that the efficacy of each parameter was as follows: preTACE arterial phase mean>postTACE delay phase Perc99>preTACE arterial phase Perc90>postTACE delay phase mean>preTACE delay phase kurtosis>postTACE delay phase Perc50>pretTACE delay phase Perc50>preTACE arterial phase Perc99. The area under the ROC curve of preTACE arterial phase mean was the highest, with a value of 0.710 (95% CI: 0.583-0.817).Conclusions The histogram features of CE-MRI can effectively evaluate and predict the characteristics of early curative effect after TACE of hepatocellular carcinoma, which helps guide clinical treatment plans.
[Keywords] hepatocellular carcinoma;magnetic resonance imaging;contrast enhanced magnetic resonance imaging;histogram analysis;texture analysis

WANG Dongdong   LI Xiaoming   YANG Liu   ZHANG Sijia*  

Department of Radiology, the Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital), Zhengzhou 450053, China

Corresponding author: ZHANG S J, E-mail: 13703923296@163.com

Conflicts of interest   None.

Received  2023-06-07
Accepted  2023-12-26
DOI: 10.12015/issn.1674-8034.2024.01.018
Cite this article as: WANG D D, LI X M, YANG L, et al. Evaluation and prediction of therapeutic effect of hepatocellular carcinoma after TACE based on contrast enhanced MRI histogram analysis[J]. Chin J Magn Reson Imaging, 2024, 15(1): 113-118, 131. DOI:10.12015/issn.1674-8034.2024.01.018.

[1]
FORNER A, REIG M, BRUIX J. Hepatocellular carcinoma[J]. Lancet, 2018, 391(10127): 1301-1314. DOI: 10.1016/S0140-6736(18)30010-2.
[2]
NAN Y M, XU X Y, GAO Y H, et al. Consensus on the secondary prevention of primary liver cancer[J]. Hepatol Int, 2021, 15(6): 1289-1300. DOI: 10.1007/s12072-021-10259-7.
[3]
RAOUL J L, FORNER A, BOLONDI L, et al. Updated use of TACE for hepatocellular carcinoma treatment: how and when to use it based on clinical evidence[J]. Cancer Treat Rev, 2019, 72: 28-36. DOI: 10.1016/j.ctrv.2018.11.002.
[4]
ZHI W H, HOU J, FAN S P, et al. Delayed biopsy following completion of transarterial chemoembolization in patients with hepatocellular carcinoma: effects on pathological outcomes and its advantages[J]. J Cancer Res Ther, 2022, 18(5): 1346-1351. DOI: 10.4103/jcrt.jcrt_732_22.
[5]
BAERE T D, ARAI Y, LENCIONI R, et al. Treatment of liver tumors with lipiodol TACE: technical recommendations from experts opinion[J]. Cardiovasc Intervent Radiol, 2016, 39(3): 334-343. DOI: 10.1007/s00270-015-1208-y.
[6]
KIM K M, KIM J H, PARK I S, et al. Reappraisal of repeated transarterial chemoembolization in the treatment of hepatocellular carcinoma with portal vein invasion[J]. J Gastroenterol Hepatol, 2009, 24(5): 806-814. DOI: 10.1111/j.1440-1746.2008.05728.x.
[7]
LIU J, PEI Y G, ZHANG Y, et al. Predicting the prognosis of hepatocellular carcinoma with the treatment of transcatheter arterial chemoembolization combined with microwave ablation using pretreatment MR imaging texture features[J]. Abdom Radiol, 2021, 46(8): 3748-3757. DOI: 10.1007/s00261-020-02891-y.
[8]
LEWIS S, HECTORS S, TAOULI B. Radiomics of hepatocellular carcinoma[J]. Abdom Radiol (NY), 2021, 46(1): 111-123. DOI: 10.1007/s00261-019-02378-5.
[9]
MAO X N, GUO Y, WEN F, et al. Applying arterial enhancement fraction (AEF) texture features to predict the tumor response in hepatocellular carcinoma (HCC) treated with Transarterial chemoembolization (TACE)[J/OL]. Cancer Imaging, 2021, 21(1): 49 [2022-06-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359085/. DOI: 10.1186/s40644-021-00418-2.
[10]
GU Y, HUANG H, TONG Q, et al. Multi-view radiomics feature fusion reveals distinct immuno-oncological characteristics and clinical prognoses in hepatocellular carcinoma[J/OL]. Cancers, 2023, 15(8): 2338. [2023-11-01]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137067/. DOI: 10.3390/cancers15082338.
[11]
AKıNCı Ö, TÜRKOGLU F, NALBANT M O, et al. The effectiveness of volumetric MRI histogram analysis in renal cell carcinoma[J]. Acad Radiol, 2023, 30(Suppl 1): S278-S285. DOI: 10.1016/j.acra.2023.03.029.
[12]
CHEN S, HARMON S, PERK T, et al. Using neighborhood gray tone difference matrix texture features on dual time point PET/CT images to differentiate malignant from benign FDG-avid solitary pulmonary nodules[J/OL]. Cancer Imaging, 2019, 19(1): 56 [2022-06-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697997/. DOI: 10.1186/s40644-019-0243-3.
[13]
GANESHAN B, SKOGEN K, PRESSNEY I, et al. Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival[J]. Clin Radiol, 2012, 67(2): 157-164. DOI: 10.1016/j.crad.2011.08.012.
[14]
CHEN J, WANG H Y, YE H Y. Research progress of texture analysis in tumor imaging[J]. Chin J Radiol, 2017, 51(12): 979-982. DOI: 10.3760/cma.j.issn.1005-1201.2017.12.020.
[15]
SHAO C C, ZHAO F, YU Y F, et al. Value of perfusion parameters and histogram analysis of triphasic computed tomography in pre-operative prediction of histological grade of hepatocellular carcinoma[J]. Chin Med J, 2021, 134(10): 1181-1190. DOI: 10.1097/CM9.0000000000001446.
[16]
ZHOU W, LV Y Z, HU X M, et al. Study on the changes of CT texture parameters before and after HCC treatment in the efficacy evaluation and survival predication of patients with HCC[J/OL]. Front Oncol, 2022, 12: 957737 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650244/. DOI: 10.3389/fonc.2022.957737.
[17]
LI L X, YANG Z H, ZHENG Y F, et al. Identification of an endoplasmic reticulum stress-related signature associated with clinical prognosis and immune therapy in glioma[J/OL]. BMC Neurol, 2022, 22(1): 192 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9131635/. DOI: 10.1186/s12883-022-02709-y.
[18]
CHOI J M, YU J S, CHO E S, et al. Texture analysis of hepatocellular carcinoma on magnetic resonance imaging: assessment for performance in predicting histopathologic grade[J]. J Comput Assist Tomogr, 2020, 44(6): 901-910. DOI: 10.1097/RCT.0000000000001087.
[19]
WANG Y M, PAN X P, LIN H, et al. Multi-scale pathology image texture signature is a prognostic factor for resectable lung adenocarcinoma: a multi-center, retrospective study[J/OL]. J Transl Med, 2022, 20(1): 595 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749333/. DOI: 10.1186/s12967-022-03777-x.
[20]
PARK H J, KIM J H, CHOI S Y, et al. Prediction of therapeutic response of hepatocellular carcinoma to transcatheter arterial chemoembolization based on pretherapeutic dynamic CT and textural findings[J]. AJR Am J Roentgenol, 2017, 209(4): W211-W220. DOI: 10.2214/AJR.16.17398.
[21]
DONG X J, GAO J L, SU W, et al. Texture analysis based on preoperative MRI to predict 47 cases of liver cancer early recurrence after transarterial chemoem-bolization[J]. J Chin Oncol, 2023, 29(2): 140-144. DOI: 10.11735/j.issn.1671-170X.2023.02.B009.
[22]
Expert Committee for the Compilation of the "Diagnosis and Treatment Standards for Primary Liver Cancer (2019 Edition)". Diagnostic and therapeutic criteria for primary liver cancer (2019 edition)[J]. Chin J Clin Med, 2020, 27(1): 140-156. DOI: 10.12025/j.issn.1008-6358.2020.20200065.
[23]
LENCIONI R, LLOVET J M. Modified RECIST (mRECIST) assessment for hepatocellular carcinoma[J]. Semin Liver Dis, 2010, 30(1): 52-60. DOI: 10.1055/s-0030-1247132.
[24]
VOSSHENRICH J, ZECH C J, HEYE T, et al. Response prediction of hepatocellular carcinoma undergoing transcatheter arterial chemoembolization: unlocking the potential of CT texture analysis through nested decision tree models[J]. Eur Radiol, 2021, 31(6): 4367-4376. DOI: 10.1007/s00330-020-07511-3.
[25]
XU Q H, ZHAO Y, WANG Y, et al. Value of texture analysis based on R2*map for predicting early recurrence of HCC after hepatectomy[J]. Chin J Magn Reson Imag, 2022, 13(12): 87-92. DOI: 10.12015/issn.1674-8034.2022.12.015.
[26]
BURCHARDT E, BOS-LIEDKE A, SERKOWSKA K, et al. Value of[18F]FDG PET/CT radiomic parameters in the context of response to chemotherapy in advanced cervical cancer[J/OL]. Sci Rep, 2023, 13(1): 9092 [2023-10-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10241798/. DOI: 10.1038/s41598-023-35843-9.
[27]
CHOI B K, PARK S, LEE G, et al. Can CT texture analysis parameters be used as imaging biomarkers for prediction of malignancy in canine splenic tumors?[J]. Vet Radiol Ultrasound, 2023, 64(2): 224-232. DOI: 10.1111/vru.13175.
[28]
LI M, FU S R, ZHU Y J, et al. Computed tomography texture analysis to facilitate therapeutic decision making in hepatocellular carcinoma[J]. Oncotarget, 2016, 7(11): 13248-13259. DOI: 10.18632/oncotarget.7467.
[29]
MĂRGINEAN L, ȘTEFAN P A, LEBOVICI A, et al. CT in the differentiation of gliomas from brain metastases: the radiomics analysis of the peritumoral zone[J/OL]. Brain Sci, 2022, 12(1): 109 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8774238/. DOI: 10.3390/brainsci12010109.
[30]
LUO Y, QIN L K, YAN J W, et al. Classification of contrast-enhanced ultrasonograms in rectal cancer according to tumor inhomogeneity using machine learning-based texture analysis[J]. Transl Cancer Res, 2022, 11(5): 1053-1063. DOI: 10.21037/tcr-21-2362.
[31]
RATHORE S, NIAZI T, IFTIKHAR M A, et al. Glioma grading via analysis of digital pathology images using machine learning[J/OL]. Cancers, 2020, 12(3): 578 [2022-06-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139732/. DOI: 10.3390/cancers12030578.
[32]
YAŞAR S, VOYVODA N, VOYVODA B, et al. Using texture analysis as a predictive factor of subtype, grade and stage of renal cell carcinoma[J]. Abdom Radiol, 2020, 45(11): 3821-3830. DOI: 10.1007/s00261-020-02495-6.
[33]
LEO A D, VARA G, PACCAPELO A, et al. Computerized tomography texture analysis of pheochromocytoma: relationship with hormonal and histopathological data[J]. J Endocrinol Invest, 2022, 45(10): 1935-1944. DOI: 10.1007/s40618-022-01826-2.
[34]
GRANATA V, FUSCO R, SETOLA S V, et al. An update on radiomics techniques in primary liver cancers[J/OL]. Infect Agent Cancer, 2022, 17(1): 6 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897888/. DOI: 10.1186/s13027-022-00422-6.
[35]
DAVNALL F, YIP C S, LJUNGQVIST G, et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice?[J]. Insights Imaging, 2012, 3(6): 573-589. DOI: 10.1007/s13244-012-0196-6.
[36]
MALSHY K, AMIEL G E, HERSHKOVITZ D, et al. Association between nuclear morphometry parameters and gleason grade in patients with prostatic cancer[J/OL]. Diagnostics, 2022, 12(6): 1356 [2023-01-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9222000/. DOI: 10.3390/diagnostics12061356.
[37]
YU J Y, ZHANG H P, TANG Z Y, et al. Value of texture analysis based on enhanced MRI for predicting an early therapeutic response to transcatheter arterial chemoembolisation combined with high-intensity focused ultrasound treatment in hepatocellular carcinoma[J/OL]. Clin Radiol, 2018, 73(8): 758.e9-758.e18 [2022-06-30]. https://sci-hub.se/10.1016/j.crad.2018.04.013. DOI: 10.1016/j.crad.2018.04.013.
[38]
TIPALDI M A, RONCONI E, LUCERTINI E, et al. Hepatocellular carcinoma drug-eluting bead transarterial chemoembolization (DEB-TACE): outcome analysis using a model based on pre-treatment CT texture features[J/OL]. Diagnostics, 2021, 11(6): 956 [2022-06-30]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226518/. DOI: 10.3390/diagnostics11060956.

PREV Value of cardiac magnetic resonance in the diagnosis of left atrial/left atrial appendage thrombosis in patients with atrial fibrillation: A systematic review and Meta-analysis
NEXT Value of ZOOM-mDixon-derived T2*/R2* imaging in preoperative predicting lymph node metastasis in pancreatic ductal adenocarcinoma
  



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