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Wang Q, Yu G, Qiu J, Lu W. Application of Intravoxel Incoherent Motion in Clinical Liver Imaging: A Literature Review. J Magn Reson Imaging 2024; 60:417-440. [PMID: 37908165 DOI: 10.1002/jmri.29086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 10/01/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
Intravoxel incoherent motion (IVIM) modeling is a widely used double-exponential model for describing diffusion-weighted imaging (DWI) signal, with a slow component related to pure molecular diffusion and a fast component associated with microcirculatory perfusion, which compensates for the limitations of traditional DWI. IVIM is a noninvasive technique for obtaining liver pathological information and characterizing liver lesions, and has potential applications in the initial diagnosis and treatment monitoring of liver diseases. Recent studies have demonstrated that IVIM-derived parameters are useful for evaluating liver lesions, including nonalcoholic fatty liver disease (NAFLD), liver fibrosis and liver tumors. However, the results are not stable. Therefore, it is necessary to summarize the current applications of IVIM in liver disease research, identify existing shortcomings, and point out the future development direction. In this review, we searched for studies related to hepatic IVIM-DWI applications over the past two decades in the PubMed database. We first introduce the fundamental principles and influential factors of IVIM, and then discuss its application in NAFLD, liver fibrosis, and focal hepatic lesions. It has been found that IVIM is still unstable in ensuring the robustness and reproducibility of measurements in the assessment of liver fibrosis grade and liver tumors differentiation, due to inconsistent and substantial overlap in the range of IVIM-derived parameters for different fibrotic stages. In the end, the future direction of IVIM-DWI in the assessment of liver diseases is discussed, emphasizing the need for further research on the stability of IVIM-derived parameters, particularly perfusion-related parameters, in order to promote the clinical practice of IVIM-DWI. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Qi Wang
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Taian, China
| | - Guanghui Yu
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian, China
| | - Weizhao Lu
- Department of Radiology, The Second Affiliated Hospital of Shandong First Medical University, Taian, China
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Jiang C, Cai YQ, Yang JJ, Ma CY, Chen JX, Huang L, Xiang Z, Wu J. Radiomics in the diagnosis and treatment of hepatocellular carcinoma. Hepatobiliary Pancreat Dis Int 2023:S1499-3872(23)00044-9. [PMID: 37019775 DOI: 10.1016/j.hbpd.2023.03.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 03/20/2023] [Indexed: 04/07/2023]
Abstract
Hepatocellular carcinoma (HCC) is a common malignant tumor. At present, early diagnosis of HCC is difficult and therapeutic methods are limited. Radiomics can achieve accurate quantitative evaluation of the lesions without invasion, and has important value in the diagnosis and treatment of HCC. Radiomics features can predict the development of cancer in patients, serve as the basis for risk stratification of HCC patients, and help clinicians distinguish similar diseases, thus improving the diagnostic accuracy. Furthermore, the prediction of the treatment outcomes helps determine the treatment plan. Radiomics is also helpful in predicting the HCC recurrence, disease-free survival and overall survival. This review summarized the role of radiomics in the diagnosis, treatment and prognosis of HCC.
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Affiliation(s)
- Chun Jiang
- Department of Clinical Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215008, China
| | - Yi-Qi Cai
- Zhejiang University School of Medicine, Hangzhou 310030, China
| | - Jia-Jia Yang
- Department of Infection Management, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215008, China
| | - Can-Yu Ma
- Zhejiang University School of Medicine, Hangzhou 310030, China
| | - Jia-Xi Chen
- Zhejiang University School of Medicine, Hangzhou 310030, China
| | - Lan Huang
- Department of Clinical Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215008, China
| | - Ze Xiang
- Zhejiang University School of Medicine, Hangzhou 310030, China
| | - Jian Wu
- Department of Clinical Laboratory, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou 215008, China.
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Guo J, Sun W, Dong C, Wu Z, Li X, Zhou R, Xu W. Intravoxel incoherent motion imaging combined with diffusion kurtosis imaging to assess the response to radiotherapy in a rabbit VX2 malignant bone tumor model. Cancer Imaging 2022; 22:47. [PMID: 36064445 PMCID: PMC9446876 DOI: 10.1186/s40644-022-00488-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/31/2022] [Indexed: 11/16/2022] Open
Abstract
Purpose To combine intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) parameters for the evaluation of radiotherapy response in rabbit VX2 malignant bone tumor model. Material and methods Forty-seven rabbits with bone tumor were prospectively enrolled and divided into pre-treatment, considerable effect and slight effect group. Treatment response was evaluated using IVIM-DKI. IVIM-based parameters (tissue diffusion [Dt], pseudo-diffusion [Dp], perfusion fraction [fp]), and DKI-based parameters (mean diffusion coefficient [MD] and mean kurtosis [MK]) were calculated for each animal. Corresponding changes in MRI parameters before and after radiotherapy in each group were studied with one-way ANOVA. Correlations of diffusion parameters of IVIM and DKI model were computed using Pearson’s correlation test. A diagnostic model combining different diffusion parameters was established using binary logistic regression, and its ROC curve was used to evaluate its diagnostic performance for determining considerable and slight effect to malignant bone tumor. Results After radiotherapy, Dt and MD increased, whereas fp and MK decreased (p < 0.05). The differences in Dt, fp, MD, and MK between considerable effect and slight effect groups were statistically significant (p < 0.05). A combination of Dt, fp, and MK had the best diagnostic performance for differentiating considerable effect from slight effect (AUC = 0.913, p < 0.001). Conclusions A combination of IVIM- and DKI-based parameters allowed the non-invasive assessment of cellular, vascular, and microstructural changes in malignant bone tumors after radiotherapy, and holds great potential for monitoring the efficacy of tumor radiotherapy. Supplementary Information The online version contains supplementary material available at 10.1186/s40644-022-00488-w.
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Affiliation(s)
- Jia Guo
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China
| | - Weikai Sun
- Department of Radiology, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Cheng Dong
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China
| | - Zengjie Wu
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China
| | - Xiaoli Li
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China
| | - Ruizhi Zhou
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China
| | - Wenjian Xu
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao, Shandong, China.
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Zhou Y, Zheng J, Yang C, Peng J, Liu N, Yang L, Zhang XM. Application of intravoxel incoherent motion diffusion-weighted imaging in hepatocellular carcinoma. World J Gastroenterol 2022; 28:3334-3345. [PMID: 36158259 PMCID: PMC9346463 DOI: 10.3748/wjg.v28.i27.3334] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/26/2022] [Accepted: 06/26/2022] [Indexed: 02/06/2023] Open
Abstract
The morbidity and mortality of hepatocellular carcinoma (HCC) rank 6th and 4th, respectively, among malignant tumors worldwide. Traditional diffusion-weighted imaging (DWI) uses the apparent diffusion coefficient (ADC) obtained by applying the monoexponential model to reflect water molecule diffusion in active tissue; however, the value of ADC is affected by microcirculation perfusion. Using a biexponential model, intravoxel incoherent motion (IVIM)-DWI quantitatively measures information related to pure water molecule diffusion and microcirculation perfusion, thus compensating for the shortcomings of DWI. The number of studies examining the application of IVIM-DWI in patients with HCC has gradually increased over the last few years, and many results show that IVIM-DWI has vital value for HCC differentiation, pathological grading, and predicting and evaluating the treatment response. The present study principally reviews the principle of IVIM-DWI and its research progress in HCC differentiation, pathological grading, predicting and evaluating the treatment response, predicting postoperative recurrence and predicting gene expression prediction.
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Affiliation(s)
- Yi Zhou
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, People's Hospital of Deyang City, Deyang 618000, Sichuan Province, China
| | - Jing Zheng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Cui Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, Panzhihua Central Hospital, Panzhihua 617000, Sichuan Province, China
| | - Juan Peng
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
- Department of Radiology, Sichuan Provincial People's Hospital Jinniu Hospital, Chengdu Jinniu District People's Hospital, Chengdu 610007, Sichuan Province, China
| | - Ning Liu
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Department of Radiology, Medical Research Center, The Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
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Wang F, Yan CY, Wang CH, Yang Y, Zhang D. The Roles of Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Diffusion-Weighted Imaging Parameters in Preoperative Evaluation of Pathological Grades and Microvascular Invasion in Hepatocellular Carcinoma. Front Oncol 2022; 12:884854. [PMID: 35646649 PMCID: PMC9131658 DOI: 10.3389/fonc.2022.884854] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 03/31/2022] [Indexed: 12/14/2022] Open
Abstract
Background Currently, there are disputes about the parameters of diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), and diffusion-weighted imaging (DWI) in predicting pathological grades and microvascular invasion (MVI) in hepatocellular carcinoma (HCC). The aim of our study was to investigate and compare the predictive power of DKI and IVIM-DWI parameters for preoperative evaluation of pathological grades and MVI in HCC. Methods PubMed, Web of Science, and Embase databases were searched for relevant studies published from inception to October 2021. Review Manager 5.3 was used to summarize standardized mean differences (SMDs) of mean kurtosis (MK), mean diffusivity (MD), tissue diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), mean apparent diffusion coefficient (ADCmean), and minimum apparent diffusion coefficient (ADCmin). Stata12.0 was used to pool the sensitivity, specificity, and area under the curve (AUC). Overall, 42 up-to-standard studies with 3,807 cases of HCC were included in the meta-analysis. Results The SMDs of ADCmean, ADCmin, and D values, but not those of D* and f values, significantly differed between well, moderately, and poorly differentiated HCC (P < 0.01). The sensitivity, specificity, and AUC of the MK, D, ADCmean, and ADCmin for preoperative prediction of poorly differentiated HCC were 69%/94%/0.89, 87%/80%/0.89, 82%/75%/0.86, and 83%/64%/0.81, respectively. In addition, the sensitivity, specificity, and AUC of the D and ADCmean for preoperative prediction of well-differentiated HCC were 87%/83%/0.92 and 82%/88%/0.90, respectively. The SMDs of ADCmean, ADCmin, D, MD, and MK values, but not f values, showed significant differences (P < 0.01) between MVI-positive (MVI+) and MVI-negative (MVI-) HCC. The sensitivity and specificity of D and ADCmean for preoperative prediction of MVI+ were 80%/80% and 74%/71%, respectively; the AUC of the D (0.87) was significantly higher than that of ADCmean (0.78) (Z = −2.208, P = 0.027). Sensitivity analysis showed that the results of the above parameters were stable and reliable, and subgroup analysis confirmed a good prediction effect. Conclusion DKI parameters (MD and MK) and IVIM-DWI parameters (D value, ADCmean, and ADCmin) can be used as a noninvasive and simple preoperative examination method to predict the grade and MVI in HCC. Compared with ADCmean and ADCmin, MD and D values have higher diagnostic efficacy in predicting the grades of HCC, and D value has superior diagnostic efficacy to ADCmean in predicting MVI+ in HCC. However, f value cannot predict the grade or MVI in HCC.
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Affiliation(s)
- Fei Wang
- Department of Medical Imaging, Luzhou People's Hospital, Luzhou, China.,Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Chun Yue Yan
- Department of Obstetrics, Luzhou People's Hospital, Luzhou, China
| | - Cai Hong Wang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Yan Yang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, Xinqiao Hospital, Third Military Medical University, Chongqing, China
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Dynamic Contrast-Enhanced and Intravoxel Incoherent Motion MRI Biomarkers Are Correlated to Survival Outcome in Advanced Hepatocellular Carcinoma. Diagnostics (Basel) 2021; 11:diagnostics11081340. [PMID: 34441274 PMCID: PMC8391260 DOI: 10.3390/diagnostics11081340] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 07/21/2021] [Accepted: 07/23/2021] [Indexed: 12/11/2022] Open
Abstract
Objective: This study assessed dynamic contrast-enhanced (DCE)-MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) parameters to prospectively predict survival outcomes in participants with advanced hepatocellular carcinoma (HCC) who received lenalidomide, a dual antiangiogenic and immunomodulatory agent, as second-line therapy in a Phase II clinical trial. Materials and methods: Forty-four participants with advanced HCC who had progression after sorafenib as first-line treatment were prospectively enrolled. Pretreatment MRI parameters—obtained from DCE-MRI (peak, slope, AUC, Ktrans, Kep, and Ve), apparent diffusion coefficient (ADC), and IVIM DWI (pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f))—were derived from the largest hepatic tumor. The Cox model was used to investigate the associations of the parameters with progression-free survival (PFS) and overall survival (OS). Results: Median PFS and OS were 2.3 and 8.0 months, respectively. Univariate analysis showed that participants with a high slope (p = 0.024), Kep (p < 0.001), and ADC (p = 0.018) values had longer PFS than those with low values; participants with a small tumor size (p = 0.006), high slope (p = 0.01), ADC (p = 0.015), and f (p = 0.012) values had longer OS than those with low values did. Cox multivariable analysis revealed that Kep (p < 0.001) and ADC (p = 0.009) remained independent predictors of PFS; slope (p = 0.003) and ADC (p = 0.009) remained independent predictors of OS. Moreover, Kep and slope were still significant after Bonferroni correction was performed (p < 0.005). Conclusion: Both pretreatment DCE-MRI and IVIM DWI parameters, especially slope and ADC, may predict PFS and OS in participants with HCC receiving lenalidomide as second-line therapy.
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The Role of Non-Gaussian Models of Diffusion Weighted MRI in Hepatocellular Carcinoma: A Systematic Review. J Clin Med 2021; 10:jcm10122641. [PMID: 34203995 PMCID: PMC8232758 DOI: 10.3390/jcm10122641] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/10/2021] [Accepted: 06/14/2021] [Indexed: 12/14/2022] Open
Abstract
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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A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma. Sci Rep 2021. [PMID: 34001962 DOI: 10.1038/s41598-021-89784-2.pmid:] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The present study aimed to investigate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in the preoperative prediction of the histologic differentiation of hepatocellular carcinoma (HCC). Seventy HCC patients were scanned with a 3.0 T magnetic resonance scanner. The values of apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and the fraction of the fast apparent diffusion coefficient (f) were measured. Analysis of variance was used to compare the differences in parameters between groups with different degrees of histologic differentiation. p < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were used to analyse the efficacy of IVIM-DWI parameters for predicting the histologic differentiation of HCC. The ADC and D values for well, moderately and poorly differentiated HCC were 1.35 ± 0.17 × 10-3 mm2/s, 1.16 ± 0.17 × 10-3 mm2/s, 0.98 ± 0.21 × 10-3 mm2/s, and 1.06 ± 0.15 × 10-3 mm2/s, 0.88 ± 0.16 × 10-3 mm2/s, 0.76 ± 0.18 × 10-3 mm2/s, respectively, and all differences were significant. The D* and f values of the three groups were 32.87 ± 14.70 × 10-3 mm2/s, 41.68 ± 17.90 × 10-3 mm2/s, 34.54 ± 18.60 × 10-3 mm2/s and 0.22 ± 0.07, 0.23 ± 0.08, 0.18 ± 0.07, respectively, with no significant difference. When the cut-off values of ADC and D were 1.25 × 10-3 mm2/s and 0.97 × 10-3 mm2/s, respectively, their diagnostic sensitivities and specificities for distinguishing well differentiated HCC from moderately differentiated and poorly differentiated HCC were 73.3%, 85.5%, 86.7%, and 78.2%, and their areas under the ROC curve were 0.821 and 0.841, respectively. ADC and D values can be used preoperatively to predict the degree of histologic differentiation in HCC, and the D value has better diagnostic value.
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Zhou Y, Yang G, Gong XQ, Tao YY, Wang R, Zheng J, Yang C, Peng J, Yang L, Li JD, Zhang XM. A study of the correlations between IVIM-DWI parameters and the histologic differentiation of hepatocellular carcinoma. Sci Rep 2021; 11:10392. [PMID: 34001962 PMCID: PMC8129092 DOI: 10.1038/s41598-021-89784-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 04/30/2021] [Indexed: 02/07/2023] Open
Abstract
The present study aimed to investigate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in the preoperative prediction of the histologic differentiation of hepatocellular carcinoma (HCC). Seventy HCC patients were scanned with a 3.0 T magnetic resonance scanner. The values of apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and the fraction of the fast apparent diffusion coefficient (f) were measured. Analysis of variance was used to compare the differences in parameters between groups with different degrees of histologic differentiation. p < 0.05 was considered statistically significant. Receiver operating characteristic (ROC) curves were used to analyse the efficacy of IVIM-DWI parameters for predicting the histologic differentiation of HCC. The ADC and D values for well, moderately and poorly differentiated HCC were 1.35 ± 0.17 × 10−3 mm2/s, 1.16 ± 0.17 × 10−3 mm2/s, 0.98 ± 0.21 × 10−3 mm2/s, and 1.06 ± 0.15 × 10−3 mm2/s, 0.88 ± 0.16 × 10−3 mm2/s, 0.76 ± 0.18 × 10−3 mm2/s, respectively, and all differences were significant. The D* and f values of the three groups were 32.87 ± 14.70 × 10−3 mm2/s, 41.68 ± 17.90 × 10−3 mm2/s, 34.54 ± 18.60 × 10−3 mm2/s and 0.22 ± 0.07, 0.23 ± 0.08, 0.18 ± 0.07, respectively, with no significant difference. When the cut-off values of ADC and D were 1.25 × 10−3 mm2/s and 0.97 × 10−3 mm2/s, respectively, their diagnostic sensitivities and specificities for distinguishing well differentiated HCC from moderately differentiated and poorly differentiated HCC were 73.3%, 85.5%, 86.7%, and 78.2%, and their areas under the ROC curve were 0.821 and 0.841, respectively. ADC and D values can be used preoperatively to predict the degree of histologic differentiation in HCC, and the D value has better diagnostic value.
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Affiliation(s)
- Yi Zhou
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China.,Department of Radiology, People's Hospital of Deyang City, Deyang, 618000, Sichuan, People's Republic of China
| | - Gang Yang
- Institute of Hepato-Biliary-Intestinal Disease, Department of Hepatobiliary Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Xue-Qin Gong
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Yun-Yun Tao
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Ran Wang
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Jing Zheng
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Cui Yang
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Juan Peng
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China.
| | - Jing-Dong Li
- Institute of Hepato-Biliary-Intestinal Disease, Department of Hepatobiliary Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
| | - Xiao-Ming Zhang
- Medical Imaging Key Laboratory of Sichuan Province, Medical Research Center, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, People's Republic of China
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Preoperatively Grading Rectal Cancer with the Combination of Intravoxel Incoherent Motions Imaging and Diffusion Kurtosis Imaging. CONTRAST MEDIA & MOLECULAR IMAGING 2020; 2020:2164509. [PMID: 33100931 PMCID: PMC7576354 DOI: 10.1155/2020/2164509] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 09/15/2020] [Accepted: 09/21/2020] [Indexed: 12/11/2022]
Abstract
Purpose To combine Intravoxel Incoherent Motions (IVIM) imaging and diffusion kurtosis imaging (DKI) which can aid in the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity to preoperatively grade rectal cancer. Methods A total of 58 rectal patients were included into this prospective study. MRI was performed with a 3T scanner. Different combinations of IVIM-derived and DKI-derived parameters were performed to grade rectal cancer. Pearson correlation coefficients were applied to evaluate the correlations. Binary logistic regression models were established via integrating different DWI parameters for screening the most sensitive parameter. Receiver operating characteristic analysis was performed for evaluating the diagnostic performance. Results For individual DWI-derived parameters, all parameters except the pseudodiffusion coefficient displayed the capability of grading rectal cancer (p < 0.05). The better discrimination between high- and low-grade rectal cancer was achieved with the combination of different DWI-derived parameters. Similarly, ROC analysis suggested the combination of D (true diffusion coefficient), f (perfusion fraction), and Kapp (apparent kurtosis coefficient) yielded the best diagnostic performance (AUC = 0.953, p < 0.001). According to the result of binary logistic analysis, cellularity-related D was the most sensitive predictor (odds ratio: 9.350 ± 2.239) for grading rectal cancer. Conclusion The combination of IVIM and DKI holds great potential in accurately grading rectal cancer as IVIM and DKI can provide the quantification of different biological inspirations including cellularity, vascularity, and microstructural heterogeneity.
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Geng Z, Zhang Y, Wang S, Li H, Zhang C, Yin S, Xie C, Dai Y. Radiomics Analysis of Susceptibility Weighted Imaging for Hepatocellular Carcinoma: Exploring the Correlation between Histopathology and Radiomics Features. Magn Reson Med Sci 2020; 20:253-263. [PMID: 32788505 PMCID: PMC8424030 DOI: 10.2463/mrms.mp.2020-0060] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Purpose: No previous researches have extracted radiomics features from susceptibility weighted imaging (SWI) for biomedical applications. This research aimed to explore the correlation between histopathology of hepatocellular carcinoma (HCC) and radiomics features extracted from SWI. Methods: A total of 53 patients were ultimately enrolled into this retrospective study with MR examinations undertaken at a 3T scanner. About 107 radiomics features were extracted from SWI images of each patient. Then, the Spearman correlation test was performed to evaluate the correlation between the SWI-derived radiomics features and histopathologic indexes including histopathologic grade, microvascular invasion (MVI) as well as the expression status of cytokeratin 7 (CK-7), cytokeratin 19 (CK-19) and Glypican-3 (GPC-3). With SWI-derived radiomics features utilized as independent variables, four logistic regression-based diagnostic models were established for diagnosing patients with positive CK-7, CK-19, GPC-3 and high histopathologic grade, respectively. Then, receiver operating characteristic analysis was performed to evaluate the diagnostic performance. Results: A total of 11, 32, 18 and one SWI-derived radiomics features were significantly correlated with histopathologic grade, the expression of CK-7, the expression of CK-19 and the expression of GPC-3 (P < 0.05), respectively. None of the SWI-derived radiomics features was correlated with MVI status. The areas under the curve were 0.905, 0.837, 0.800 and 0.760 for diagnosing patients with positive CK-19, positive CK-7, high histopathologic grade and positive GPC-3. Conclusion: Extracting the radiomics features from SWI images was feasible to evaluate multiple histopathologic indexes of HCC.
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Affiliation(s)
- Zhijun Geng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center.,Department of Radiology, Sun Yat-sen University Cancer Center
| | - Yunfei Zhang
- Central Research Institute, United Imaging Healthcare
| | - Shutong Wang
- Department of Hepatic Surgery, First Affiliated Hospital of Sun Yat-sen University
| | - Hui Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center.,Department of Radiology, Sun Yat-sen University Cancer Center
| | - Cheng Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center.,Department of Radiology, Sun Yat-sen University Cancer Center
| | - Shaohan Yin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center.,Department of Radiology, Sun Yat-sen University Cancer Center
| | - Chuanmiao Xie
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center.,Department of Radiology, Sun Yat-sen University Cancer Center
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare
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12
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Shi G, Han X, Wang Q, Ding Y, Liu H, Zhang Y, Dai Y. Evaluation of Multiple Prognostic Factors of Hepatocellular Carcinoma with Intra-Voxel Incoherent Motions Imaging by Extracting the Histogram Metrics. Cancer Manag Res 2020; 12:6019-6031. [PMID: 32765101 PMCID: PMC7381091 DOI: 10.2147/cmar.s262973] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 06/26/2020] [Indexed: 12/11/2022] Open
Abstract
Purpose To predict multiple prognostic factors of HCC including histopathologic grade, the expression of Ki67 as well as capsule formation with intravoxel incoherent motions imaging by extracting the histogram metrics. Patients and Methods A total of 52 patients with HCC were recruited with the MR examinations undertaken at a 3T scanner. Histogram metrics were extracted from IVIM-derived parametric maps. Independent student t-test was performed to explore the differences in metrics across different subtypes of prognostic factors. Spearman correlation test was utilized to evaluate the correlations between the IVIM metrics and prognostic factors. ROC analysis was applied to evaluate the diagnostic performance. Results According to the independent student t-test, there were 18, 4, and 8 IVIM-derived histogram metrics showing the capability for differentiating the subtypes of histopathologic grade, Ki67, and capsule formation, respectively, with P-values of less than 0.05. Besides, there existed a lot of significant correlations between IVIM metrics and prognostic factors. Finally, by integrating different histogram metrics showing significant differences between various subgroups together via establishing logistic regression based diagnostic models, greatest diagnostic power was obtained for grading HCC (AUC=0.917), diagnosing patients with highly expressed Ki67 (AUC=0.861) and diagnosing patients with capsule formation (AUC=0.839). Conclusion Multiple prognostic factors including histopathologic grade, Ki67 expression status, and capsule formation can be accurately predicted with assistance of histogram metrics sourced from a single IVIM scan.
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Affiliation(s)
- Gaofeng Shi
- Department of Radiology, Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, People's Republic of China
| | - Xue Han
- Department of Radiology, Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, People's Republic of China
| | - Qi Wang
- Department of Radiology, Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, People's Republic of China
| | - Yan Ding
- Department of Radiology, Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, People's Republic of China
| | - Hui Liu
- Department of Radiology, Fourth Hospital of Hebei Medical University, Shijiazhuang 050000, People's Republic of China
| | - Yunfei Zhang
- Department of Research Collaboration Hospital (MRI), Central Research Institute, United Imaging Healthcare, Shanghai 201800, People's Republic of China
| | - Yongming Dai
- Department of Research Collaboration Hospital (MRI), Central Research Institute, United Imaging Healthcare, Shanghai 201800, People's Republic of China
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13
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Hu K, Lu S, Li M, Zhang F, Tang B, Yuan J, Shan Y, Xu P, Chen R, Ren Z, Yin X. A Novel Pre-treatment Model Predicting Risk of Developing Refractoriness to Transarterial Chemoembolization in Unresectable Hepatocellular Carcinoma. J Cancer 2020; 11:4589-4596. [PMID: 32489476 PMCID: PMC7255373 DOI: 10.7150/jca.44847] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 05/02/2020] [Indexed: 12/16/2022] Open
Abstract
Background and aim: Refractoriness to transarterial chemoembolization is common during the therapeutic process of hepatocellular carcinoma, which is an intractable issue and may compromise the prognosis. We aim to establish a pre-treatment model to identify patients with high risks of refractoriness. Methods: From 2010 to 2016, 824 treatment-naive patients who had initially underwent at least two sessions of transarterial chemoembolization in Zhongshan Hospital, Fudan University were retrospectively enrolled. These patients were randomly allocated into a training cohort and a validation cohort. The pre-treatment scoring model was established based on the clinical and radiological variables using logistic regression and nomogram. The discrimination and calibration of the model were also evaluated. Results: Logistic regression identified vascularization pattern, ALBI grade, serum alpha-fetoprotein level, serum γ-glutamyl transpeptidase level and major tumor size as the key parameters related to refractoriness. The p-TACE model was established using these variables (risk score range: 0-19.5). Patients were divided into six risk subgroups based on their scores (<4, ≥4, ≥7, ≥10, ≥13, ≥16). The discriminative ability, as determined by the area under receiver operating characteristic curve was 0.784 (95% confidence interval: 0.741-0.827) in the training cohort and 0.743 (95% confidence interval: 0.696-0.789) in the validation cohort. Moreover, satisfactory calibration was confirmed by Hosmer-Lemeshow test with P values of 0.767 and 0.913 in the training cohort and validation cohort. Conclusions: This study presents a pre-treatment model to identify patients with high risks of refractoriness after transarterial chemoembolization and shed light on clinical decision making.
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Affiliation(s)
- Keshu Hu
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Shenxin Lu
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Miao Li
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Feng Zhang
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Bei Tang
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Jia Yuan
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Yan Shan
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Pengju Xu
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Rongxin Chen
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Zhenggang Ren
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
| | - Xin Yin
- Liver Cancer Institute & Zhongshan Hospital, Fudan University, Shanghai, China; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education
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14
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Shan Q, Kuang S, Zhang Y, He B, Wu J, Zhang T, Wang J. A comparative study of monoexponential versus biexponential models of diffusion-weighted imaging in differentiating histologic grades of hepatitis B virus-related hepatocellular carcinoma. Abdom Radiol (NY) 2020; 45:90-100. [PMID: 31595327 DOI: 10.1007/s00261-019-02253-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE To compare the diagnostic value of apparent diffusion coefficient (ADC) and intravoxel incoherent motion metrics in discriminating histologic grades of hepatocellular carcinoma (HCC) in patients with hepatitis B virus (HBV) infection. METHODS 117 chronic HBV patients with 120 pathologically confirmed HCCs after surgical resection or liver transplantation were enrolled in this retrospective study. Diffusion-weighted imaging was performed using eleven b values (0-1500 s/mm2) and two b values (0, 800 s/mm2) successively on a 3.0 T system. ADC0, 800, ADCtotal, diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were calculated. The parameters of three histologically differentiated subtypes were investigated using Kruskal-Wallis test, Spearman rank correlation, and receiver-operating characteristic analysis. Interobserver agreement was assessed using the intraclass correlation coefficient. RESULTS There was excellent agreement for ADCtotal/D/f, good agreement for ADC0,800, and moderate agreement for D*. ADCtotal, ADC0, 800,D, and f were significantly different for well, moderately, and poorly differentiated HCCs (P < 0.001), and they were all inversely correlated with histologic grades: r = - 0.633, - 0.394, - 0.435, and - 0.358, respectively (P < 0.001). ADCtotal demonstrated higher performance than ADC0,800 in diagnosing both well and poorly differentiated HCCs (P < 0.001 and P = 0.04, respectively). ADCtotal showed higher performance than D and f in diagnosing well differentiated HCCs (P < 0.001) and similar performance in diagnosing poorly differentiated HCCs (P = 0.06 and 0.13, respectively). CONCLUSIONS ADCtotal showed better diagnostic performance than ADC0,800, D, and f to discriminate histologic grades of HCC.
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Affiliation(s)
- Qungang Shan
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China
| | - Sichi Kuang
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China
| | - Yao Zhang
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China
| | - Bingjun He
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China
| | - Jun Wu
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China
| | - Tianhui Zhang
- Department of Radiology, MeiZhou People's Hospital, Meizhou Affiliated Hospital of Sun Yat-Sen University, Huangtang Road, Meizhou, 514031, Guangdong, People's Republic of China
| | - Jin Wang
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd., Guangzhou, 510630, Guangdong, People's Republic of China.
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15
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Yang D, She H, Wang X, Yang Z, Wang Z. Diagnostic accuracy of quantitative diffusion parameters in the pathological grading of hepatocellular carcinoma: A meta-analysis. J Magn Reson Imaging 2019; 51:1581-1593. [PMID: 31654537 DOI: 10.1002/jmri.26963] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 09/21/2019] [Accepted: 09/23/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Accurate preoperative assessment of the pathological grade of hepatocellular carcinoma (HCC) could greatly benefit prognostic predictions. PURPOSE To assess and compare the diagnostic accuracy of the apparent diffusion coefficient (ADC) and tissue diffusivity (D) for the noninvasive pathological grading of HCC. STUDY TYPE Meta-analysis. DATA SOURCES PubMed/Medline, EMBASE, the Web of Science, and the Cochrane Library were searched to find related original articles published up to May 30, 2019. FIELD STRENGTH/SEQUENCE Diffusion-weighted imaging (DWI) and/or intravoxel incoherent motion (IVIM) were performed with a 1.5T or 3.0T scanner. ASSESSMENT The Quality Assessment of Diagnostic Accuracy Studies 2 tool was used to assess the methodologic quality. STATISTICAL TESTS The bivariate random-effects model was used to obtain the pooled sensitivity and specificity, and the area under summary receiver operating characteristic curve (AUROC) was obtained. Subgroup analyses were performed. RESULTS A total of 16 original articles (1428 HCCs) were included. Most studies had a low to unclear risk of bias and minimal concerns regarding applicability. For the discrimination of well-differentiated HCCs, the pooled sensitivity and specificity of the ADC value were 85% and 92%, respectively. For the discrimination of poorly differentiated HCCs, the pooled sensitivity and specificity of the ADC value and D were 84% and 80%, and 92% and 77%, respectively. The summary AUROC of D (0.94) was significantly higher than that of ADC (0.89) (z = -2.718, P = 0.007). The subgroup analyses identified three covariates including size, number of included lesions in the studies, and blindness to the reference standard as possible sources of heterogeneity. DATA CONCLUSION This meta-analysis showed that the ADC and D values had a high to excellent accuracy for the noninvasive pathological grading of HCCs and that the D value was superior to the ADC value for discriminating poorly differentiated HCCs. LEVEL OF EVIDENCE 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1581-1593.
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Affiliation(s)
- Dawei Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Hualong She
- Department of Radiology, Affiliated Hospital of Xiangnan University, Chenzhou, China
| | - Xiaopei Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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16
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Shao S, Shan Q, Zheng N, Wang B, Wang J. Role of Intravoxel Incoherent Motion in Discriminating Hepatitis B Virus-Related Intrahepatic Mass-Forming Cholangiocarcinoma from Hepatocellular Carcinoma Based on Liver Imaging Reporting and Data System v2018. Cancer Biother Radiopharm 2019; 34:511-518. [PMID: 31314589 DOI: 10.1089/cbr.2019.2799] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Backgroud: Intravoxel incoherent motion (IVIM) could be used to characterize benign and malignant hepatic lesions and predict the histological grade of hepatocellular carcinoma (HCC). To evaluate IVIM-derived parameters for differentiating between hepatitis B virus (HBV)-related intrahepatic mass-forming cholangiocarcinoma (IMCC) and HCC based on the Liver Imaging Reporting and Data System (LI-RADS) v2018. Materials and Methods: 20 IMCC patients and one-to-one matched control HCC patients were retrospectively assessed. IVIM scanning with 11 b-values (from 0 to 1500 s/mm2) was obtained using a 3.0-T magnetic resonance scanner. Apparent diffusion coefficient (ADC) and IVIM parameters, including diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f), were compared between IMCC and HCC. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performances of ADC, D, f, and D*. The LI-RADS features and a final category were also compared using LI-RADS v2018. Results: ADC and D were significantly higher in IMCC than in HCC (p = 0.012 and p = 0.007, respectively); f was significantly higher in HCC than in IMCC (p = 0.004). The area under the ROC curve values for ADC, D, and f for differentiating HBV-related IMCC from HCC were 0.724, 0.753, and 0.741, respectively. Conclusion: The majority of HBV-related IMCCs can be categorized as LR-M by using LI-RADS. However, atypical IMCCs may be classified as non-LR-M. ADC, D, and f values may be helpful in differentiating HBV-related IMCC from HCC, and similar diagnostic performances were obtained for these values.
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Affiliation(s)
- Shuo Shao
- Shandong Medical Imaging Research Institute, Shandong University, Jinan, P.R. China.,Department of Radiology, Jining No. 1 People's Hospital, Jining, P.R. China
| | - Qungang Shan
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), Guangzhou, P.R. China
| | - Ning Zheng
- Department of Radiology, Jining No. 1 People's Hospital, Jining, P.R. China
| | - Bin Wang
- Medical Imaging Research Institute, Binzhou Medical University, Yantai, P.R. China
| | - Jin Wang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University (SYSU), Guangzhou, P.R. China
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17
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Granata V, Fusco R, Filice S, Catalano O, Piccirillo M, Palaia R, Izzo F, Petrillo A. The current role and future prospectives of functional parameters by diffusion weighted imaging in the assessment of histologic grade of HCC. Infect Agent Cancer 2018; 13:23. [PMID: 29988667 PMCID: PMC6029348 DOI: 10.1186/s13027-018-0194-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Accepted: 06/22/2018] [Indexed: 12/17/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is one of the most common human solid malignancies worldwide. Although the MRI is the technique that is best adapted to characterize HCC, there is not an agreement regarding the study protocol and even what the role of Diffusion-weighted imaging (DWI). The possibility that imaging study can correlate to histologic grade to selecting the therapeutic strategy would be valuable in helping to direct the proper management of HCC. Apparent Diffusion Coefficient (ADC) and IVIM-derived perfusion fraction (fp) and tissue diffusivity (Dt) values of HCC showed significantly better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and significant correlation was observed between ADC, fp, Dt and histological grade.
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Affiliation(s)
- Vincenza Granata
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Roberta Fusco
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy.,2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Salvatore Filice
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Orlando Catalano
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Mauro Piccirillo
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Raffaele Palaia
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Francesco Izzo
- 2Hepatobiliary Surgical Oncology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
| | - Antonella Petrillo
- 1Radiology Division, Istituto Nazionale Tumori IRCCS Fondazione G. Pascale - IRCCS di Napoli, via Mariano Semmola, I-80131 Naples, Italy
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18
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Park IK, Yu JS, Cho ES, Kim JH, Chung JJ. Apparent diffusion coefficient of hepatocellular carcinoma on diffusion-weighted imaging: Histopathologic tumor grade versus arterial vascularity during dynamic magnetic resonance imaging. PLoS One 2018; 13:e0197070. [PMID: 29750794 PMCID: PMC5947906 DOI: 10.1371/journal.pone.0197070] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2017] [Accepted: 03/13/2018] [Indexed: 12/16/2022] Open
Abstract
Objectives Apparent diffusion coefficient (ADC) has been suggested to reflect the tumor grades of hepatocellular carcinomas (HCCs); i.e., it can be used as a biomarker to predict the patients’ prognosis. To verify its feasibility as a biomarker, the present study sought to determine how the ADC values of HCC are affected by a tumor’s histopathologic grade and arterial vascularity. Materials and methods From 131 consecutive patients, 141 surgically resected HCCs (16 well-differentiated [wd-HCCs], 83 moderately-differentiated [md-HCCs], and 42 poorly-differentiated HCCs [pd-HCCs]) were subjected to a comparison of the tumors’ arterial vascularity (non-, slightly-, or markedly-hypervascular) determined on dynamic magnetic resonance imaging (MRI) and the ADC was measured retrospectively. Results The pd-HCCs (1.05±0.16 × 10−3 mm2/s) had a significantly lower ADC than md-HCCs (1.16±0.21 × 10−3 mm2/s; p = 0.010), but there was no significant difference compared to wd-HCCs (1.11±0.18 × 10−3 mm2/s; p = 0.968). The mean ADC was significantly higher in markedly hypervascular lesions (1.20±0.20 × 10−3 mm2/s) than in nonhypervascular lesions (0.95±0.14 × 10−3mm2/s; p<0.001) or slightly hypervascular lesions (1.04±0.15 × 10−3mm2/s; p<0.001). The ADC values and arterial vascularity were significantly correlated in wd-HCCs (p = 0.005) and md-HCCs (p<0.001). The mean ADC of pd-HCCs was significantly lower than those of other lesions, even in the markedly hypervascular lesion subgroup (p = 0.020). Conclusion Although pd-HCC constantly shows low ADCs regardless of arterial vascularities, ADCs cannot stably stratify histopathologic tumor grades due to the variable features of wd-HCCs; and the ADC should be used with caution as a tumor biomarker of HCC.
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Affiliation(s)
- In Kyung Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-Gu, Seoul, Korea
| | - Jeong-Sik Yu
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-Gu, Seoul, Korea
- * E-mail:
| | - Eun-Suk Cho
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-Gu, Seoul, Korea
| | - Joo Hee Kim
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-Gu, Seoul, Korea
| | - Jae-Joon Chung
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Gangnam-Gu, Seoul, Korea
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