Pre-TACE kurtosis of ADCtotal derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma

Wu, Lifang; Rao, Sheng-Xiang; Xu, Pengju; Yang, Li; Chen, Caizhong; Líu, Hao; Huang, Jianfeng; Fu, Caixia; Halim, Alice; Zeng, Mengsu

doi:10.1007/s00330-018-5482-3

Cited by 26 publications

(14 citation statements)

References 31 publications

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“…Posttreatment MRI scanning was performed for each patient. Tumor response to TACE was evaluated based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST), 23 and patients with stable or progressive disease were classified into the nonresponse group, while patients with complete or partial response were classified into the response group 24 …”

Section: Methodsmentioning

confidence: 99%

Prediction Model for Intermediate‐Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization

Jia

Yan

et al. 2020

Magnetic Resonance Imaging

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Background: The outcome of intermediate-stage hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) is greatly heterogeneous. Current means for predicting HCC response to TACE are lacking. Purpose: To investigate whether the combination of parameters derived from amide proton transfer (APT) and intravoxel incoherent motion (IVIM) imaging, and morphological characteristics of tumor can establish a better prediction model than the univariant model for HCC response to TACE. Study Type: Prospective. Subjects: 56 patients with intermediate-stage HCC (50 males and six females). Field Strength/Sequences: 3.0T; T 2-weighted-fast spin echo, 3D liver acquisition with volume flex, single-shot fast spin echo-planar imaging (EPI), spin echo-EPI. Assessment: Pretreatment APT signal intensities (SIs), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) for tumor, peritumoral, and normal tissues were measured. Follow-up MRI scanning was performed, and the patients were classified as responders or nonresponders based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria. Statistical Tests: The imaging parameters were compared among the three tissues and between the two groups using analysis of variance (ANOVA) or two-sample t-test. The prediction model's variables were derived from univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance. Results: Based on the logistic regression analysis results, we established a prediction model that integrated the APT SI and D values in the tumor tissue and the tumor size. ROC analyses revealed that the model was better able to predict tumor response to TACE (area under the ROC curve = 0.851) than the individual parameters on their own. Data Conclusion: A prediction model incorporating pretreatment APT SI, D in the tumor tissue and tumor size may be useful for predicting the response of intermediate-stage HCC to TACE. Level of Evidence: 1 Technical Efficacy: Stage 1

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Section: Methodsmentioning

confidence: 99%

Prediction Model for Intermediate‐Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization

Jia

Yan

et al. 2020

Magnetic Resonance Imaging

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“…Among the 33 studies, 11 investigated IVIM for HCC diagnosis, namely for HCC detection respect to normal liver parenchyma or other types of hepatic lesions (either benign or malignant), and seven evaluated the power of IVIM parameters for HCC histological grading. Among the 15 remaining studies, six assessed the usefulness of IVIM for the response of HCC to therapy [40,42,48,66,69,73], five evaluated if IVIM could be associated with prognostic factors [51,52,56,58,67], and four explored IVIM model for multiple aims [37,41,53,64] (two investigated response to therapy and survival [53,64], one on grading and prognostic factors [41], and the remaining one on diagnosis and grading [37]).…”

Section: Studies On Ivimmentioning

confidence: 99%

“…They found that the D value before treatment could be a valuable biomarker for predicting the therapeutic effects of sorafenib for HCC. Two studies aimed to assess response to therapy of HCC patients performing a histogram analysis of IVIM metrics [42,53]. Hectors et al involved HCC patients treated by yttrium 90 radioembolization and found that D* and D could be used to evaluate HCC response to radioembolization.…”

Section: Response To Therapymentioning

confidence: 99%

“…D was also associated with progression free survival of HCC TACE-treated patients in study by Wu et al [64], even if similar performances were shown by ADC. In a subsequent study performed by the same group, they investigated if histogram-based IVIM features could be associated with HCC time to progression, but any significant results were found [53]. Finally, Kakite et al [67] assessed the diagnostic performance of IVIM parameters for prediction of complete tumor necrosis, finding a significant positive correlation between D and tumor necrosis.…”

Section: Prognosismentioning

confidence: 99%

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The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review

Tramontano

Cavaliere

Salvatore

et al. 2021

JCM

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The importance of Diffusion Weighted Imaging (DWI) in hepatocellular carcinoma (HCC) has been widely handled in the literature. Due to the mono-exponential model limitations, several studies recently investigated the role of non-Gaussian DWI models in HCC. However, their results are variable and inconsistent. Therefore, the aim of this systematic review is to summarize current knowledge on non-Gaussian DWI techniques in HCC. A systematic search of the literature, including PubMed, Google Scholar, MEDLINE, and ScienceDirect databases, was performed to identify original articles since 2010 that evaluated the role of non-Gaussian DWI models for HCC diagnosis, grading, response to treatment, and prognosis. Studies were grouped and summarized according to the non-Gaussian DWI models investigated. We focused on the most used non-Gaussian DWI models (Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Stretched Exponential—SE). The quality of included studies was evaluated by using QUADAS-2 and QUIPS tools. Forty-three articles were included, with IVIM and DKI being the most investigated models. Although the role of non-Gaussian DWI models in clinical settings has not fully been established, our findings showed that their parameters may potentially play a role in HCC. Further studies are required to identify a standardized DWI acquisition protocol for HCC diagnosis, grading, response to treatment, and prognosis.

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“…The study by Park et al[ 89 ] showed that the D* value could reflect the blood supply of HCC and predict the deposition effect of iodide oil after TACE surgery; the D* value and arterial enhancement ratio (AER) of preoperative lesions in the group with better iodized oil deposition were significantly higher than those in the group with poor iodized oil deposition. Wu et al[ 92 ] believed that the ADC maybe the best independent predictor of TACE treatment responses.…”

Section: Evaluation Of the Hcc Treatment Responsementioning

confidence: 99%

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

Tao¹,

Zhou²,

Wang³

et al. 2020

WJCC

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Traditional magnetic resonance (MR) diffusion-weighted imaging (DWI) uses a single exponential model to obtain the apparent diffusion coefficient to quantitatively reflect the diffusion motion of water molecules in living tissues, but it is affected by blood perfusion. Intravoxel incoherent motion (IVIM)-DWI utilizes a double-exponential model to obtain information on pure water molecule diffusion and microcirculatory perfusion-related diffusion, which compensates for the insufficiency of traditional DWI. In recent years, research on the application of IVIM-DWI in the diagnosis and treatment of hepatic diseases has gradually increased and has achieved considerable progress. This study mainly reviews the basic principles of IVIM-DWI and related research progress in the diagnosis and treatment of hepatic diseases.

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Pre-TACE kurtosis of ADCtotal derived from histogram analysis for diffusion-weighted imaging is the best independent predictor of prognosis in hepatocellular carcinoma

Abstract: • mRECIST was associated with TTP independently. • Lower kurtosis and higher mean for ADCs tend to have good response. • Pre-TACE kurtosis of ADC is the best independent predictor for TTP.

Cited by 26 publications

References 31 publications

Prediction Model for Intermediate‐Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization

Prediction Model for Intermediate‐Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization

The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review

Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases

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