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For: Choi IY, Lee SS, Sung YS, Cheong H, Lee H, Byun JH, Kim SY, Lee SJ, Shin YM, Lee MG. Intravoxel incoherent motion diffusion-weighted imaging for characterizing focal hepatic lesions: Correlation with lesion enhancement. J Magn Reson Imaging 2016;45:1589-1598. [PMID: 27664970 DOI: 10.1002/jmri.25492] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Accepted: 09/10/2016] [Indexed: 12/21/2022] Open

For:	Choi IY, Lee SS, Sung YS, Cheong H, Lee H, Byun JH, Kim SY, Lee SJ, Shin YM, Lee MG. Intravoxel incoherent motion diffusion-weighted imaging for characterizing focal hepatic lesions: Correlation with lesion enhancement. J Magn Reson Imaging 2016;45:1589-1598. [PMID: 27664970 DOI: 10.1002/jmri.25492] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Accepted: 09/10/2016] [Indexed: 12/21/2022] Open

Number

Cited by Other Article(s)

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: 2] [Impact Index Per Article: 2.0] [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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Liu N, Wu Y, Tao Y, Zheng J, Huang X, Yang L, Zhang X. Differentiation of Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma through MRI Radiomics. Cancers (Basel) 2023;15:5373. [PMID: 38001633 PMCID: PMC10670473 DOI: 10.3390/cancers15225373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 10/25/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open

Abstract

The purpose of this study was to investigate the efficacy of magnetic resonance imaging (MRI) radiomics in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The clinical and MRI data of 129 pathologically confirmed HCC patients and 48 ICC patients treated at the Affiliated Hospital of North Sichuan Medical College between April 2016 and December 2021 were retrospectively analyzed. The patients were randomly divided at a ratio of 7:3 into a training group of 124 patients (90 with HCC and 34 with ICC) and a validation group of 53 patients (39 with HCC and 14 with ICC). Radiomic features were extracted from axial fat suppression T2-weighted imaging (FS-T2WI) and axial arterial-phase (AP) and portal-venous-phase (PVP) dynamic-contrast-enhanced MRI (DCE-MRI) sequences, and the corresponding datasets were generated. The least absolute shrinkage and selection operator (LASSO) method was used to select the best radiomic features. Logistic regression was used to establish radiomic models for each sequence (FS-T2WI, AP and PVP models), a clinical model for optimal clinical variables (C model) and a joint radiomics model (JR model) integrating the radiomics features of all the sequences as well as a radiomics-clinical model combining optimal radiomic features and clinical risk factors (RC model). The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC). The AUCs of the FS-T2WI, AP, PVP, JR, C and RC models for distinguishing HCC from ICC were 0.693, 0.863, 0.818, 0.914, 0.936 and 0.977 in the training group and 0.690, 0.784, 0.727, 0.802, 0.860 and 0.877 in the validation group, respectively. The results of this study suggest that MRI-based radiomics may help noninvasively differentiate HCC from ICC. The model integrating the radiomics features and clinical risk factors showed a further improvement in performance.

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Affiliation(s)

Ning Liu Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.) Hospital of Chengdu Office of People’s Government of Tibetan Autonomous Region (Hospital. C.T.), Chengdu 610041, China
Yaokun Wu Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)
Yunyun Tao Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)
Jing Zheng Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)
Xiaohua Huang Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)
Lin Yang Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)
Xiaoming Zhang Medical Imaging Key Laboratory of Sichuan Province, Interventional Medical Center, Department of Radiology, Medical Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China; (N.L.); (Y.W.); (Y.T.); (J.Z.); (X.H.); (X.Z.)

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Song M, Wang Q, Feng H, Wang L, Zhang Y, Liu H. Preoperative Grading of Rectal Cancer with Multiple DWI Models, DWI-Derived Biological Markers, and Machine Learning Classifiers. Bioengineering (Basel) 2023;10:1298. [PMID: 38002422 PMCID: PMC10669695 DOI: 10.3390/bioengineering10111298] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 10/05/2023] [Accepted: 10/25/2023] [Indexed: 11/26/2023] Open

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: 0.7] [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: 06/23/2022] [Indexed: 02/06/2023] Open

Value of Intravoxel Incoherent Motion (IVIM) Imaging for Differentiation between Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma. CONTRAST MEDIA & MOLECULAR IMAGING 2022;2022:1504463. [PMID: 35615729 PMCID: PMC9113914 DOI: 10.1155/2022/1504463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 03/21/2022] [Accepted: 04/22/2022] [Indexed: 12/19/2022]

Abstract

Efficient noninvasive imaging techniques in the differentiation of intrahepatic cholangiocarcinoma (ICC) and hepatocellular carcinoma (HCC) are very important because of their different management and prognosis. Our purpose was to evaluate the difference of parameters extracted from intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) between the two groups and their performance for the differentiation, as well as the significance of perfusion information. IVIM studies (9 b-values) in 41 patients with either ICC or HCC were reviewed retrospectively by two observers. Diffusion coefficient (D), pseudodiffusion coefficient (D∗), perfusion fraction (f), ADC, and the mean percentage of parenchymal enhancement (MPPE) at 30 s after contrast-enhancement were calculated and compared between ICC and HCC. The relationship between D∗, f values, and MPPE was evaluated by Spearman's correlation test. The diagnostic efficacy of all parameters was analyzed by the receiver operating characteristic (ROC) curve. Interobserver and intraobserver agreements were analyzed. The parameters (D and ADC) of ICC were distinctly higher than those of HCC; whereas the parameters (f and MPPE of arterial phase) were distinctly lower (all false discovery rate [FDR]-corrected P < 0.05). The metric D∗ value of ICC was slightly higher than that of HCC (71.44 vs 69.41) with FDR-corrected P > 0.05. Moreover, the value of parameter D was significantly lower than that of ADC (FDR-corrected P < 0.05). The parameters (D and f values) extracted from IVIM showed excellent diagnostic efficiency in the identification, and the diagnostic efficiency of D value was significantly higher than that of the ADC. There were positive correlations between perfusion-related parameters (D∗, f values) and MPPE. Interobserver and intraobserver agreements were excellent or perfect in measurements of all parameters. Parameters derived from IVIM were valuable for distinguishing ICC and HCC. Moreover, the D value showed better diagnostic efficiency for the differential diagnosis than monoexponential fitting-derived ADC value. Meanwhile, the significant correlation between perfusion-related parameters and MPPE demonstrates that specific IVIM metrics may serve as a noninvasive indicator for the vascular perfusion information of ICC and HCC.

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Çelebi F, Görmez A, Serkan Ilgun A, Tokat Y, Cem Balcı N. The role of 18F- FDG PET/MRI in preoperative prediction of MVI in patients with HCC. Eur J Radiol 2022;149:110196. [DOI: 10.1016/j.ejrad.2022.110196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/30/2022] [Accepted: 02/01/2022] [Indexed: 12/12/2022]

Mürtz P, Mesropyan N, Sprinkart AM, Block W, Luetkens JA, Attenberger U, Pieper CC. Simplified intravoxel incoherent motion diffusion-weighted MRI of liver lesions: feasibility of combined two-colour index maps. Eur Radiol Exp 2021;5:33. [PMID: 34368913 PMCID: PMC8349945 DOI: 10.1186/s41747-021-00233-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/03/2021] [Indexed: 11/10/2022] Open

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: 9] [Impact Index Per Article: 2.3] [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

Fujimoto K, Noda Y, Kawai N, Kajita K, Akamine Y, Kawada H, Hyodo F, Matsuo M. Comparison of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted MR imaging models in differentiating hepatic hemangiomas from liver metastases. Eur J Radiol 2021;141:109806. [PMID: 34120012 DOI: 10.1016/j.ejrad.2021.109806] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 03/22/2021] [Accepted: 05/31/2021] [Indexed: 11/15/2022]

Abstract

PURPOSE

This study aims to compare the diagnostic values of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) in differentiating hepatic hemangiomas and liver metastases.

METHOD

This prospective study was approved by our institutional review board, and written informed consent was obtained from all patients. In this study, 244 patients with known or suspected liver disease underwent magnetic resonance imaging. Among them, 37 patients who had focal hepatic lesions with a maximum diameter of ≥10 mm were evaluated. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for the three models: the apparent diffusion coefficient (ADC) from a mono-exponential model; the true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from a bi-exponential model; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from a stretched exponential model. The parameters were compared between hepatic hemangiomas and liver metastases.

RESULTS

In total, 64 focal hepatic lesions were evaluated, of which 22 were identified to be hepatic hemangiomas and 42 were liver metastases. ADC, D, f, and DDC values were significantly lower in liver metastases than in hepatic hemangiomas (P <  0.0001, <  0.0001, 0.015, and <  0.0001, respectively); whereas, the α value was significantly higher in liver metastases than in hepatic hemangiomas (P =  0.028). The areas under the ROC curve (AUCs) for differentiating hepatic hemangiomas and liver metastases in ADC, D, D*, f, DDC, and α were 0.940, 0.908, 0.608, 0.686, 0.952, and 0.667, respectively. The AUC values of ADC and DDC were significantly greater than those of D* (P <  0.0001), f (P =  0.0001), and α values (P =  0.0001).

CONCLUSION

ADC and DDC values from the mono-exponential and stretched exponential models could be considered as quantitative imaging biomarkers for differentiating hepatic hemangiomas and liver metastases.

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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: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [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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Cannella R, Sartoris R, Grégory J, Garzelli L, Vilgrain V, Ronot M, Dioguardi Burgio M. Quantitative magnetic resonance imaging for focal liver lesions: bridging the gap between research and clinical practice. Br J Radiol 2021;94:20210220. [PMID: 33989042 PMCID: PMC8173689 DOI: 10.1259/bjr.20210220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open

Shi GZ, Chen H, Zeng WK, Gao M, Wang MZ, Zhang HT, Shen J. R2* value derived from multi-echo Dixon technique can aid discrimination between benign and malignant focal liver lesions. World J Gastroenterol 2021;27:1182-1193. [PMID: 33828393 PMCID: PMC8006098 DOI: 10.3748/wjg.v27.i12.1182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 02/02/2021] [Accepted: 02/25/2021] [Indexed: 02/06/2023] Open

Abstract

BACKGROUND

R2* estimation reflects the paramagnetism of the tumor tissue, which may be used to differentiate between benign and malignant liver lesions when contrast agents are contraindicated.

AIM

To investigate whether R2* derived from multi-echo Dixon imaging can aid differentiating benign from malignant focal liver lesions (FLLs) and the impact of 2D region of interest (2D-ROI) and volume of interest (VOI) on the outcomes.

METHODS

We retrospectively enrolled 73 patients with 108 benign or malignant FLLs. All patients underwent conventional abdominal magnetic resonance imaging and multi-echo Dixon imaging. Two radiologists independently measured the mean R2* values of lesions using 2D-ROI and VOI approaches. The Bland–Altman plot was used to determine the interobserver agreement between R2* measurements. Intraclass correlation coefficient (ICC) was used to determine the reliability between the two readers. Mean R2* values were compared between benign and malignant FFLs using the nonparametric Mann–Whitney test. Receiver operating characteristic curve analysis was used to determine the diagnostic performance of R2* in differentiation between benign and malignant FFLs. We compared the diagnostic performance of R2* measured by 2D-ROI and VOI approaches.

RESULTS

This study included 30 benign and 78 malignant FLLs. The interobserver reproducibility of R2* measurements was excellent for the 2D-ROI (ICC = 0.994) and VOI (ICC = 0.998) methods. Bland–Altman analysis also demonstrated excellent agreement. Mean R2* was significantly higher for malignant than benign FFLs as measured by 2D-ROI (P < 0.001) and VOI (P < 0.001). The area under the curve (AUC) of R2* measured by 2D-ROI was 0.884 at a cut-off of 25.2/s, with a sensitivity of 84.6% and specificity of 80.0% for differentiating benign from malignant FFLs. R2* measured by VOI yielded an AUC of 0.875 at a cut-off of 26.7/s in distinguishing benign from malignant FFLs, with a sensitivity of 85.9% and specificity of 76.7%. The AUCs of R2* were not significantly different between the 2D-ROI and VOI methods.

CONCLUSION

R2* derived from multi-echo Dixon imaging whether by 2D-ROI or VOI can aid in differentiation between benign and malignant FLLs.

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Kovač JD, Daković M, Janković A, Mitrović M, Dugalić V, Galun D, Đurić-Stefanović A, Mašulović D. The role of quantitative diffusion-weighted imaging in characterization of hypovascular liver lesions: A prospective comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. PLoS One 2021;16:e0247301. [PMID: 33606753 PMCID: PMC7894812 DOI: 10.1371/journal.pone.0247301] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 02/04/2021] [Indexed: 11/18/2022] Open

Tao YY, Zhou Y, Wang R, Gong XQ, Zheng J, Yang C, Yang L, Zhang XM. Progress of intravoxel incoherent motion diffusion-weighted imaging in liver diseases. World J Clin Cases 2020;8:3164-3176. [PMID: 32874971 PMCID: PMC7441263 DOI: 10.12998/wjcc.v8.i15.3164] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 06/11/2020] [Accepted: 07/14/2020] [Indexed: 02/05/2023] Open

Peng J, Zheng J, Yang C, Wang R, Zhou Y, Tao YY, Gong XQ, Wang WC, Zhang XM, Yang L. Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma. Sci Rep 2020. [DOI: doi.org/10.1038/s41598-020-64804-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open

Peng J, Zheng J, Yang C, Wang R, Zhou Y, Tao YY, Gong XQ, Wang WC, Zhang XM, Yang L. Intravoxel incoherent motion diffusion-weighted imaging to differentiate hepatocellular carcinoma from intrahepatic cholangiocarcinoma. Sci Rep 2020;10:7717. [PMID: 32382050 PMCID: PMC7206040 DOI: 10.1038/s41598-020-64804-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 04/20/2020] [Indexed: 02/08/2023] Open

Noda Y, Goshima S, Fujimoto K, Akamine Y, Kajita K, Kawai N, Matsuo M. Comparison of the Diagnostic Value of Mono-exponential, Bi-exponential, and Stretched Exponential Signal Models in Diffusion-weighted MR Imaging for Differentiating Benign and Malignant Hepatic Lesions. Magn Reson Med Sci 2020;20:69-75. [PMID: 32161202 PMCID: PMC7952197 DOI: 10.2463/mrms.mp.2019-0151] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open

Wu M, Zhou RH, Xu F, Li XP, Zhao P, Yuan R, Lan YP, Zhou WX. Multi-parameter ultrasound based on the logistic regression model in the differential diagnosis of hepatocellular adenoma and focal nodular hyperplasia. World J Gastrointest Oncol 2019;11:1193-1205. [PMID: 31908724 PMCID: PMC6937441 DOI: 10.4251/wjgo.v11.i12.1193] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/13/2019] [Accepted: 09/10/2019] [Indexed: 02/05/2023] Open

Abstract

BACKGROUND

Focal nodular hyperplasia (FNH) has very low potential risk, and a tendency to spontaneously resolve. Hepatocellular adenoma (HCA) has a certain malignant tendency, and its prognosis is significantly different from FNH. Accurate identification of HCA and FNH is critical for clinical treatment.

AIM

To analyze the value of multi-parameter ultrasound index based on logistic regression for the differential diagnosis of HCA and FNH.

METHODS

Thirty-one patients with HCA were included in the HCA group. Fifty patients with FNH were included in the FNH group. The clinical data were collected and recorded in the two groups. Conventional ultrasound, shear wave elastography, and contrast-enhanced ultrasound were performed, and the lesion location, lesion echo, Young’s modulus (YM) value, YM ratio, and changes of time intense curve (TIC) were recorded. Multivariate logistic regression analysis was used to screen the indicators that can be used for the differential diagnosis of HCA and FNH. A ROC curve was established for the potential indicators to analyze the accuracy of the differential diagnosis of HCA and FNH. The value of the combined indicators for distinguishing HCA and FNH were explored.

RESULTS

Multivariate logistic regression analysis showed that lesion echo (P = 0.000), YM value (P = 0.000) and TIC decreasing slope (P = 0.000) were the potential indicators identifying HCA and FNH. In the ROC curve analysis, the accuracy of the YM value distinguishing HCA and FNH was the highest (AUC = 0.891), which was significantly higher than the AUC of the lesion echo and the TIC decreasing slope (P < 0.05). The accuracy of the combined diagnosis was the highest (AUC = 0.938), which was significantly higher than the AUC of the indicators diagnosing HCA individually (P < 0.05). This sensitivity was 91.23%, and the specificity was 83.33%.

CONCLUSION

The combination of lesion echo, YM value and TIC decreasing slope can accurately differentiate between HCA and FNH.

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Wáng YXJ, Wang X, Wu P, Wang Y, Chen W, Chen H, Li J. Topics on quantitative liver magnetic resonance imaging. Quant Imaging Med Surg 2019;9:1840-1890. [PMID: 31867237 DOI: 10.21037/qims.2019.09.18] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]

Wei Y, Huang Z, Tang H, Deng L, Yuan Y, Li J, Wu D, Wei X, Song B. IVIM improves preoperative assessment of microvascular invasion in HCC. Eur Radiol 2019;29:5403-5414. [PMID: 30877465 DOI: 10.1007/s00330-019-06088-w] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 02/02/2019] [Accepted: 02/08/2019] [Indexed: 02/05/2023]

Abstract

PURPOSE

To prospectively evaluate the potential role of intravoxel incoherent motion (IVIM) and conventional radiologic features for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).

METHODS

Institutional review board approval and written informed consent were obtained for this study. A cohort comprising 115 patients with 135 newly diagnosed HCCs between January 2016 and April 2017 were evaluated. Two radiologists independently reviewed the radiologic features and the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion component fraction (f) were also measured. Interobserver agreement was checked and univariate and multivariate logistic regressions were used for screening the risk factors. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.

RESULTS

Features significantly related to MVI of HCC at univariate analysis were reduced ADC (odds ratio, 0.341; 95% CI, 0.211-0.552; p < 0.001), D (odds ratio, 0.141; 95% CI, 0.067-0.299; p < 0.001), and irregular circumferential enhancement (odds ratio, 9.908; 95% CI, 3.776-25.996; p < 0.001). At multivariate analysis, only D value (odds ratio, 0.096; 95% CI, 0.025-0.364; p < 0.001) was the independent risk factor for MVI of HCC. The mean D value for MVI of HCC showed an area under ROC curves of 0.815 (95% CI, 0.740-0.877).

CONCLUSION

IVIM model-derived D value is superior to ADC measured with mono-exponential model for evaluating the MVI of HCC. Among MR imaging features, tumor margin, enhancement pattern, tumor capsule, and peritumoral enhancement were not predictive for MVI.

KEY POINTS

• Diffusion MRI is useful for non-invasively evaluating the microvascular invasion of hepatocellular carcinoma. • IVIM model is advantageous over mono-exponential model for assessing the microvascular invasion of hepatocellular carcinoma. • Decreased D value was the independent risk factor for predicting MVI of HCC.

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Wagner M, Doblas S, Poté N, Lambert SA, Ronot M, Garteiser P, Paradis V, Vilgrain V, Van Beers BE. Comparison of pulsed and oscillating gradient diffusion-weighted MRI for characterizing hepatocellular nodules in liver cirrhosis: ex vivo study in a rat model. J Magn Reson Imaging 2019;51:1065-1074. [PMID: 31507025 DOI: 10.1002/jmri.26919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 08/07/2019] [Indexed: 12/30/2022] Open

Abstract

BACKGROUND

In contrast to classical pulsed gradient diffusion-weighted MRI, oscillating gradient diffusion-weighted MR imaging (DWI) is sensitive to short distance diffusion changes at the intracellular level.

PURPOSE

To compare the diagnostic performance of pulsed and oscillating DWI for characterizing hepatocellular nodules in a rat model of hepatic cirrhosis.

STUDY TYPE

Prospective, experimental study.

ANIMAL MODEL

Cirrhosis was induced by weekly intraperitoneal injection of diethylnitrosamine in Wistar rats.

FIELD STRENGTH/SEQUENCE

Ex vivo liver MRI was performed at 7T with T₁ -weighted, T₂ -weighted, pulsed, and oscillating gradient diffusion-weighted sequences.

ASSESSMENT

Apparent diffusion coefficient from pulsed (ADC_pulsed ) and oscillating gradient (ADC_oscillating ) sequences was calculated in 82 nodules identified on the T₁ /T₂ -weighted images and on pathological examination. Two pathologists classified the nodules in three categories: benign (regenerative and low-grade dysplastic nodules), with intermediate malignancy (high-grade dysplastic nodules and early hepatocellular carcinomas) and overtly malignant (progressed hepatocellular carcinomas).

STATISTICAL TESTS

Differences between groups were assessed with Kruskal-Wallis and Mann-Whitney tests.

RESULTS

ADC, mainly ADC_oscillating , increased in the group of nodules with intermediate malignancy (ADC_pulsed : 0.75 ± 0.25 × 10^-3 mm² /s vs. 0.64 ± 0.07 × 10^-3 mm² /s in benign nodules, P = 0.025; ADC_oscillating : 0.81 ± 0.20 × 10^-3 mm² /s vs. 0.65 ± 0.13 × 10^-3 mm² /s, P = 0.0008) and ADC_pulsed decreased in the group of progressed hepatocellular carcinomas (ADC_pulsed : 0.60 ± 0.08 × 10^-3 mm² /s, P = 0.042; ADC_oscillating : 0.68 ± 0.08 × 10^-3 mm² /s, P = 0.1).

DATA CONCLUSION

ADC during hepatocarcinogenesis in rats increased in nodules with intermediate malignancy and decreased in progressed hepatocellular carcinomas. Our results suggest that oscillating gradient DWI is more sensitive to the early steps of hepatocarcinogenesis and might be useful for differentiating between high-grade dysplastic nodules / early hepatocellular carcinomas and regenerating nodules / low-grade dysplastic nodules.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1065-1074.

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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: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open

Hong EK, Joo I, Park J, Lee K. Assessment of hepatic sinusoidal obstruction syndrome with intravoxel incoherent motion diffusion-weighted imaging: An experimental study in a rat model. J Magn Reson Imaging 2019;51:81-89. [PMID: 31094055 DOI: 10.1002/jmri.26790] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 04/29/2019] [Accepted: 04/29/2019] [Indexed: 02/06/2023] Open

Abstract

BACKGROUND

Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) parameters may reflect perfusion and diffusion changes in hepatic sinusoidal obstruction syndrome (SOS).

PURPOSE

To investigate the feasibility of IVIM-DWI in the noninvasive assessment of hepatic SOS in an experimental rat model.

STUDY TYPE

Animal study.

POPULATION/SUBJECTS

Forty-four rats were administered different doses (90 or 160 mg/kg) of monocrotaline by gavage either 48 or 72 hours before MRI to induce different degrees of hepatic SOS, and another 10 rats served as controls.

FIELD STRENGTH/SEQUENCE

3T scanner, IVIM-DWI using nine b values (0-800 sec/mm² ).

ASSESSMENT

Histologically, rats were classified as having none (n = 10), mild (n = 8), moderate (n = 19), or severe SOS (n = 17). The apparent diffusion coefficient (ADC) and IVIM-derived parameters (D: true diffusion coefficient, D*: pseudo-diffusion coefficient, and f: perfusion fraction) of the liver parenchyma were measured.

STATISTICAL TESTS

IVIM-DWI parameters were compared according to histologic grades of SOS (none, mild, moderate, and severe), and receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic accuracy.

RESULTS

ADC, D, and f of the liver parenchyma were significantly different according to SOS severity groups (Ps < 0.01) and significantly decreased as SOS severity increased (rho = -0.323, -0.313, and -0.700; P = 0.017, 0.021, and <0.001, respectively). Means of f in none, mild, moderate, and severe SOS were 17.2%, 13.3%, 12.3%, and 11.1%, respectively. Among ADC and IVIM-derived parameters, f provided the highest area under the ROC curves for detecting ≥mild, ≥moderate, and severe SOS (0.991, 0.890, and 0.803, respectively).

DATA CONCLUSION

IVIM-DWI may be useful in the diagnosis and severity assessment of hepatic SOS.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:81-89.

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Kim HC, Seo N, Chung YE, Park MS, Choi JY, Kim MJ. Characterization of focal liver lesions using the stretched exponential model: comparison with monoexponential and biexponential diffusion-weighted magnetic resonance imaging. Eur Radiol 2019;29:5111-5120. [PMID: 30796578 DOI: 10.1007/s00330-019-06048-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Revised: 12/23/2018] [Accepted: 01/25/2019] [Indexed: 01/17/2023]

Abstract

OBJECTIVE

To compare the stretched exponential model of diffusion-weighted imaging (DWI) with monoexponential and biexponential models in terms of the ability to characterize focal liver lesions (FLLs).

METHODS

This retrospective study included 180 patients with FLLs who underwent magnetic resonance imaging including DWI with nine b values at 3.0 T. The distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched exponential model; true diffusion coefficient (D_t), pseudo-diffusion coefficient (D_p), and perfusion fraction (f) from a biexponential model; and apparent diffusion coefficient (ADC) were calculated for each lesion. Diagnostic performances of the parameters were assessed through receiver operating characteristic (ROC) analysis. For 20 patients with treated hepatic metastases, the correlation between the DWI parameters and the percentage of tumor necrosis on pathology was evaluated using the Spearman correlation coefficient.

RESULTS

DDC had the highest area under the ROC curve (AUC, 0.905) for differentiating malignant from benign lesions, followed by D_t (0.903) and ADC (0.866), without significant differences among them (DDC vs. D_t, p = 0.946; DDC vs. ADC, p = 0.157). For distinguishing hypovascular from hypervascular lesions, and hepatocellular carcinoma from metastasis, f had a significantly higher AUC than the other DWI parameters (p < 0.05). The α had the strongest correlation with the degree of tumor necrosis (ρ = 0.655, p = 0.002).

CONCLUSION

The DDC from stretched exponential model of DWI demonstrated excellent diagnostic performance for differentiating malignant from benign FLLs. The α is promising for evaluating the degree of necrosis in treated metastases.

KEY POINTS

• The stretched exponential DWI model is valuable for characterizing focal liver lesions. • The DDC from stretched exponential model shows excellent performance for differentiating malignant from benign focal liver lesions. • The α from stretched exponential model is promising for evaluating the degree of necrosis in hepatic metastases after chemotherapy.

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