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For: 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: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [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

For:	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: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [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

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Cited by Other Article(s)

Zhang K, He K, Zhang L, Li WC, Xie SS, Cui YZ, Lin LY, Shen ZW, Xia S, Su XM, Zhang HM, Ye ZX, Shen W. Gadoxetic Acid-enhanced MRI Scoring Model to Predict Pathologic Features of Hepatocellular Carcinoma. Radiology 2025;314:e233229. [PMID: 39932410 DOI: 10.1148/radiol.233229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2025]

Abstract

Background Prediction of high-risk pathologic features such as microvascular invasion (MVI), poorly differentiated pathologic grade (poor PG), and satellite nodules (SNs) has significant clinical value, as these features are associated with early recurrence and metastasis in hepatocellular carcinoma (HCC). Purpose To develop and validate a preoperative scoring model using gadoxetic acid-enhanced MRI features for noninvasive prediction of HCC high-risk pathologic features and early recurrence. Materials and Methods This retrospective study included consecutive patients with HCC who underwent preoperative gadoxetic acid-enhanced MRI at three centers (one training dataset and two external validation datasets) between January 2014 and January 2021. The preoperative imaging characteristics of each patient were evaluated via multivariable logistic regression, using surgical specimen pathologic evaluation as the reference standard, for prediction of MVI, poor PG, and SNs. In the training dataset, eight intratumoral features, three peritumoral features, and three laboratory indicators were initially evaluated. A scoring model was developed based on the results of the logistic regression, with the following imaging features demonstrating significant independent association with high-risk pathologic features: diameter greater than 4.0 cm, irregular morphology, intratumoral arteries, peritumoral enhancement in the arterial phase, and low peritumoral signal intensity. The resulting score, called the Image score (I-score), to predict early recurrence of HCC in patients was further validated in an outcome dataset. Results A total of 366 patients (median age, 57 years [IQR, 49-64 years]; 314 men, 52 women) from the three centers were included in the training dataset (n = 150), two external validation datasets (n = 73 and 56), and outcome dataset (n = 87). The area under the receiver operating characteristic curve (AUC) of the I-score for predicting high-risk pathologic features was 0.93 (95% CI: 0.88, 0.97) in the training dataset and 0.86 (95% CI: 0.76, 0.93) and 0.84 (95% CI: 0.72, 0.92) in the two external datasets. In the outcome dataset, the I-score was an independent predictor of early recurrence (hazard ratio, 5.2 [95% CI: 1.9, 14.2]; P = .002). A combined model including the I-score and two other predictors demonstrated superior prognostic performance (C index, 0.84 [95% CI: 0.74, 0.91]). Conclusion The developed scoring model based on gadoxetic acid-enhanced MRI enabled noninvasive preoperative prediction of HCC high-risk pathologic features and early recurrence. © RSNA, 2025 Supplemental material is available for this article.

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Affiliation(s)

Kun Zhang From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Kan He From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Lei Zhang From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Wen-Cui Li From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Shuang-Shuang Xie From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Ying-Zhu Cui From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Li-Ying Lin From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Zhi-Wei Shen From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Shuang Xia From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Xiao-Min Su From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Hui-Mao Zhang From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Zhao-Xiang Ye From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)
Wen Shen From the Department of Radiology, Medical Imaging Institute of Tianjin, Tianjin First Central Hospital, School of Medicine, Nankai University, 24 Fukang Rd, Nankai District, Tianjin 300192, China (K.Z., S.S.X., L.Y.L., S.X., W.S.); Department of Radiology, First Hospital of Jilin University, Changchun, China (K.H., L.Z., Y.Z.C., H.M.Z.); Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Tianjin Key Laboratory of Digestive Cancer, Tianjin, China (W.C.L., Z.X.Y.); State Key Laboratory of Druggability Evaluation and Systematic Translational Medicine, Tianjin, China (W.C.L., Z.X.Y.); Tianjin's Clinical Research Center for Cancer, Tianjin, China (W.C.L., Z.X.Y.); Philips Healthcare, Beijing, China (Z.W.S.); and Department of Immunology, Nankai University School of Medicine, Nankai University, Tianjin, China (X.M.S.)

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Cui G, Liu W, Sun X, Bai Y, Ding M, Zhao N, Guo J, Qu D, Wang S, Qin L, Yang Y. RNA-seq shows Angiopoietin-like 4 promotes hepatocellular carcinoma progression by inducing M2 polarization of tumor-associated macrophages. Int J Biol Macromol 2025;287:138523. [PMID: 39653221 DOI: 10.1016/j.ijbiomac.2024.138523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 12/01/2024] [Accepted: 12/05/2024] [Indexed: 12/15/2024]

Lu M, Wang C, Zhuo Y, Gou J, Li Y, Li J, Dong X. Preoperative prediction power of radiomics and non-radiomics methods based on MRI for early recurrence in hepatocellular carcinoma: a systemic review and meta-analysis. Abdom Radiol (NY) 2024;49:3397-3411. [PMID: 38704783 DOI: 10.1007/s00261-024-04356-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/21/2024] [Accepted: 04/21/2024] [Indexed: 05/07/2024]

Abstract

OBJECTIVE

To compare radiomics and non-radiomics in predicting early recurrence (ER) in patients with hepatocellular carcinoma (HCC) after curative surgery.

METHODS

We systematically searched PubMed and Embase databases. Studies with clear reference criteria were selected. Data were extracted and assessed for quality using the quality in prognosis studies tool (QUIPS) by two independent authors. All included radiomics studies underwent radiomics quality score (RQS) assessment. We calculated sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) using random or fixed models with a 95%CI. Forest maps visualized the data, and summary receiver operating characteristic (sROC) curves with the area under the curve (AUC) were generated. Meta-regression and subgroup analyses explored sources of heterogeneity. We compared sensitivity, specificity, PLR, and NLR using the z-test and compared AUC values using the Delong test.

RESULTS

Our meta-analysis included 10 studies comprising 1857 patients. For radiomics, the pooled sensitivity, specificity, AUC of sROC, PLR and NLR were 0.84(95%CI: 0.78-0.89), 0.80(95%CI: 0.75-0.85), 0.89(95%CI: 0.86-0.91), 4.28(95%CI: 3.48-5.27) and 0.20(95%CI: 0.14-0.27), respectively, but with significant heterogeneity (I2 = 60.78% for sensitivity, I2 = 55.79% for specificity) and potential publication bias (P = 0.04). The pooled sensitivity, specificity, AUC of sROC, PLR, NLR for non-radiomics were 0.75(95%CI:0.68-0.81), 0.78(95%CI:0.72-0.83), 0.83(95%CI: 0.80-0.86), 3.45(95%CI: 2.68-4.44) and 0.32(95%CI: 0.24-0.41), respectively. There was no significant heterogeneity in this group (I2 = 0% for sensitivity, I2 = 17.27% for specificity). Radiomics showed higher diagnostic accuracy (AUC: 0.89 vs. 0.83, P = 0.0456), higher sensitivity (0.84 vs. 0.75, P = 0.0385) and lower NLR (0.20 vs. 0.32, P = 0.0287).

CONCLUSION

The radiomics from preoperative MRI effectively predicts ER of HCC and has higher diagnostic accuracy than non-radiomics. Due to potential publication bias and suboptimal RQS scores in radiomics, these results should be interpreted cautiously.

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Song T, Lu S, Qu J, Zhang H, Wang Z, Jia Z, Li H, Zhao Y, Qin J, Feng W, Wang S, Yan X. Intravoxel incoherent motion diffusion-weighted imaging in evaluating preoperative staging of esophageal squamous cell carcinoma : Evaluation of preoperative stage of primary tumour and prediction of lymph node metastases from esophageal cancer using IVIM: a prospective study. Cancer Imaging 2024;24:116. [PMID: 39210470 PMCID: PMC11363402 DOI: 10.1186/s40644-024-00765-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 08/26/2024] [Indexed: 09/04/2024] Open

Abstract

BACKGROUND

The aim of this research is to prospectively investigate the diagnostic performance of intravoxel incoherent motion (IVIM) using the integrated slice-specific dynamic shimming (iShim) technique in staging primary esophageal squamous cell carcinoma (ESCC) and predicting presence of lymph node metastases from ESCC.

METHODS

Sixty-three patients with ESCC were prospectively enrolled from April 2016 to April 2019. MR and IVIM using iShim technique (b = 0, 25, 50, 75, 100, 200, 400, 600, 800 s/mm2) were performed on 3.0T MRI system before operation. Primary tumour apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f) were measured by two independent radiologists. The differences in D, D*, f and ADC values of different T and N stages were assessed. Intraclass correlation coefficients (ICCs) were calculated to evaluate the interobserver agreement between two readers. The diagnostic performances of D, D*, f and ADC values in primary tumour staging and prediction of lymph node metastasis of ESCC were determined using receiver operating characteristic (ROC) curve analysis.

RESULTS

The inter-observer consensus was excellent for IVIM parameters and ADC (D: ICC = 0.922; D*: ICC = 0.892; f: ICC = 0.948; ADC: ICC = 0.958). The ADC, D, D* and f values of group T1 + T2 were significantly higher than those of group T3 + T4a [ADC: (2.55 ± 0.43) ×10- 3 mm2/s vs. (2.27 ± 0.40) ×10- 3 mm2/s, t = 2.670, P = 0.010; D: (1.82 ± 0.39) ×10- 3 mm2/s vs. (1.53 ± 0.33) ×10- 3 mm2/s, t = 3.189, P = 0.002; D*: 46.45 (30.30,55.53) ×10- 3 mm2/s vs. 32.30 (18.60,40.95) ×10- 3 mm2/s, z=-2.408, P = 0.016; f: 0.45 ± 0.12 vs. 0.37 ± 0.12, t = 2.538, P = 0.014]. The ADC, D and f values of the lymph nodes-positive (N+) group were significantly lower than those of lymph nodes-negative (N0) group [ADC: (2.10 ± 0.33) ×10- 3 mm2/s vs. (2.55 ± 0.40) ×10- 3 mm2/s, t=-4.564, P < 0.001; D: (1.44 ± 0.30) ×10- 3 mm2/s vs. (1.78 ± 0.37) ×10- 3 mm2/s, t=-3.726, P < 0.001; f: 0.32 ± 0.10 vs. 0.45 ± 0.11, t=-4.524, P < 0.001]. The combination of D, D* and f yielded the highest area under the curve (AUC) (0.814) in distinguishing group T1 + T2 from group T3 + T4a. D combined with f provided the highest diagnostic performance (AUC = 0.849) in identifying group N + and group N0 of ESCC.

CONCLUSIONS

IVIM may be used as an effective functional imaging technique to evaluate preoperative stage of primary tumour and predict presence of lymph node metastases from ESCC.

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Liu X, Wang YF, Qi XH, Zhang ZL, Pan JY, Fan XL, Du Y, Zhai YM, Wang Q. Reproducibility study of intravoxel incoherent motion and apparent diffusion coefficient parameters in normal pancreas. World J Gastrointest Surg 2024;16:2031-2039. [PMID: 39087122 PMCID: PMC11287683 DOI: 10.4240/wjgs.v16.i7.2031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/11/2024] [Accepted: 05/27/2024] [Indexed: 07/22/2024] Open

Abstract

BACKGROUND

The consistency of pancreatic apparent diffusion coefficient (ADC) values and intravoxel incoherent motion (IVIM) parameter values across different magnetic resonance imaging (MRI) devices significantly impacts the patient's diagnosis and treatment.

AIM

To explore consistency in image quality, ADC values, and IVIM parameter values among different MRI devices in pancreatic examinations.

METHODS

This retrospective study was approved by the local ethics committee, and informed consent was obtained from all participants. In total, 22 healthy volunteers (10 males and 12 females) aged 24-61 years (mean, 28.9 ± 2.3 years) underwent pancreatic diffusion-weighted imaging using 3.0T MRI equipment from three vendors. Two independent observers subjectively scored image quality and measured the pancreas's overall ADC values and signal-to-noise ratios (SNRs). Subsequently, regions of interest (ROIs) were delineated for the IVIM parameters (true diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction) using post-processing software. These ROIs were on the head, body, and tail of the pancrease. The subjective image ratings were assessed using the kappa consistency test. Intraclass correlation coefficients (ICCs) and mixed linear models were used to evaluate each device's quantitative parameter values. Finally, a pairwise analysis of IVIM parameter values across each device was performed using Bland-Altman plots.

RESULTS

The Kappa value for the subjective ratings of the different observers was 0.776 (P < 0.05). The ICC values for inter-observer and intra-observer agreements for the quantitative parameters were 0.803 [95% confidence interval (CI): 0.684-0.880] and 0.883 (95%CI: 0.760-0.945), respectively (P < 0.05). The ICCs for the SNR between different devices was comparable (P > 0.05), and the ICCs for the ADC values from different devices were 0.870, 0.707, and 0.808, respectively (P < 0.05). Notably, only a few statistically significant inter-device agreements were observed for different IVIM parameters, and among those, the ICC values were generally low. The mixed linear model results indicated differences (P < 0.05) in the f-value for the pancreas head, D-value for the pancreas body, and D-value for the pancreas tail obtained using different MRI machines. The Bland-Altman plots showed significant variability at some data points.

CONCLUSION

ADC values are consistent among different devices, but the IVIM parameters' repeatability is moderate. Therefore, the variability in the IVIM parameter values may be associated with using different MRI machines. Thus, caution should be exercised when using IVIM parameter values to assess the pancreas.

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Zhang K, Li WC, Xie SS, Lin LY, Shen ZW, Ye ZX, Shen W. Preoperative determination of pathological grades of primary single HCC: development and validation of a scoring model. ABDOMINAL RADIOLOGY (NEW YORK) 2022;47:3468-3477. [PMID: 35842888 DOI: 10.1007/s00261-022-03606-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 01/18/2023]

Deng Y, Li J, Xu H, Ren A, Wang Z, Yang D, Yang Z. Diagnostic Accuracy of the Apparent Diffusion Coefficient for Microvascular Invasion in Hepatocellular Carcinoma: A Meta-analysis. J Clin Transl Hepatol 2022;10:642-650. [PMID: 36062283 PMCID: PMC9396311 DOI: 10.14218/jcth.2021.00254] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 10/13/2021] [Accepted: 10/27/2021] [Indexed: 12/04/2022] 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

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: 1.7] [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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Ma XH, Chen K, Wang S, Liu SY, Li DF, Mi YT, Wu ZY, Qu CF, Zhao XM. Bi-specific T1 positive-contrast-enhanced magnetic resonance imaging molecular probe for hepatocellular carcinoma in an orthotopic mouse model. World J Gastrointest Oncol 2022;14:858-871. [PMID: 35582105 PMCID: PMC9048532 DOI: 10.4251/wjgo.v14.i4.858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 08/31/2021] [Accepted: 03/14/2022] [Indexed: 02/06/2023] Open

Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality. HCC-targeted magnetic resonance imaging (MRI) is an effective noninvasive diagnostic method that involves targeting clinically-related HCC biomarkers, such as alpha-fetoprotein (AFP) or glypican-3 (GPC3), with iron oxide nanoparticles. However, in vivo studies of HCC-targeted MRI utilize single-target iron oxide nanoprobes as negative (T2) contrast agents, which might weaken their future clinical applications due to tumor heterogeneity and negative MRI contrast. Ultra-small superparamagnetic iron oxide (USPIO) nanoparticles (approximately 5 nm) are potential optimal positive (T1) contrast agents. We previously verified the efficiency of AFP/GPC3-double-antibody-labeled iron oxide MR molecular probe in vitro.

AIM

To validate the effectiveness of a bi-specific probe in vivo for enhancing T1-weighted positive contrast to diagnose the early-stage HCC.

METHODS

The single- and double-antibody-conjugated 5-nm USPIO probes, including anti-AFP-USPIO (UA), anti-GPC3-USPIO (UG), and anti-AFP-USPIO-anti-GPC3 (UAG), were synthesized. T1- and T2-weighted MRI were performed on day 10 after establishment of the orthotopic HCC mouse model. Following intravenous injection of U, UA, UG, and UAG probes, T1- and T2-weighted images were obtained at 12, 12, and 32 h post-injection. At the end of scanning, mice were euthanized, and a histologic analysis was performed on tumor samples.

RESULTS

T1- and T2-weighted MRI showed that absolute tumor-to-background ratios in UAG-treated HCC mice peaked at 24 h post-injection, with the T1- and T2-weighted signals increasing by 46.7% and decreasing by 11.1%, respectively, relative to pre-injection levels. Additionally, T1-weighted contrast in the UAG-treated group at 24 h post-injection was enhanced 1.52-, 2.64-, and 4.38-fold compared to those observed for single-targeted anti-GPC3-USPIO, anti-AFP-USPIO, and non-targeted USPIO probes, respectively. Comparison of U-, UA-, UG-, and UAG-treated tumor sections revealed that UAG-treated mice exhibited increased stained regions compared to those observed in UG- or UA-treated mice.

CONCLUSION

The bi-specific T1-positive contrast-enhanced MRI probe (UAG) for HCC demonstrated increased specificity and sensitivity to diagnose early-stage HCC irrespective of tumor size and/or heterogeneity.

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Perfusion-Diffusion Ratio: A New IVIM Approach in Differentiating Solid Benign and Malignant Primary Lesions of the Liver. BIOMED RESEARCH INTERNATIONAL 2022;2022:2957759. [PMID: 35075424 PMCID: PMC8783718 DOI: 10.1155/2022/2957759] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/02/2021] [Accepted: 11/30/2021] [Indexed: 12/14/2022]

Deng Y, Yang D, Xu H, Ren A, Yang Z. Diagnostic performance of imaging features in the HBP of gadoxetate disodium-enhanced MRI for microvascular invasion in hepatocellular carcinoma: a meta-analysis. Acta Radiol 2021;63:1303-1314. [PMID: 34459669 DOI: 10.1177/02841851211038806] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]

Nalaini F, Shahbazi F, Mousavinezhad SM, Ansari A, Salehi M. Diagnostic accuracy of apparent diffusion coefficient (ADC) value in differentiating malignant from benign solid liver lesions: a systematic review and meta-analysis. Br J Radiol 2021;94:20210059. [PMID: 34111960 DOI: 10.1259/bjr.20210059] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open

Abstract

OBJECTIVES

We undertook a systematic review and meta-analysis of the diagnostic performance of mean apparent diffusion coefficient (ADC) values derived by diffusion-weighted (DW)-MRI in the characterization of solid benign and malignant liver lesions, and to assess their value in discriminating these lesions in daily routine practice.

METHODS

A systematic review of PubMed, Embase, Scopus, and Web of Science was conducted to retrieve studies that used ADC values for differentiating solid benign/dysplastic nodules and malignant liver lesions. A bivariate random-effects model with pooled sensitivity and specificity values with 95% CI (confidence interval) was used. This meta-analysis was performed on the per-lesion basis. Summary receiver operating characteristic (SROC) plot and area under curve (AUC) were created.

RESULTS

A total of 14 original articles were retrieved. The combined (95% CI) sensitivity and specificity of mean ADC values for differentiating solid benign from malignant lesions were 78% (67-86%) and 74% (64-81%), respectively. The pooled (95% CI) positive and negative LRs were respectively 3 (2.3-3.8) and 0.3 (0.21-0.43). The DOR (95% CI) was 10 (7-15). The AUC (95% CI) of the SROC plot was 82% (78-85%). Reporting bias was negligible (p value of regression test = 0.36). Mean size of malignant lesions and breathing pattern of MRI were found to be sources of heterogeneity of pooled sensitivity.

CONCLUSION

ADC measurement independently may not be an optimal diagnostic imaging method for differentiating solid malignant from solid benign hepatic lesions. The meta-analysis showed that ADC measurement had moderate diagnostic accuracy for characterizing solid liver lesions. Further prospective and comparative studies with pre-specified ADC thresholds could be performed to investigate the best MRI protocol and ADC threshold for characterizing solid liver lesions.

ADVANCES IN KNOWLEDGE

ADC measurement by DW-MRI does not have a good diagnostic performance to differentiate solid malignant from solid benign lesions. Therefore, we suggest not using ADC values in clinical practice to evaluate solid liver lesions.

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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

Chen K, She HL, Wu T, Hu F, Li T, Luo LP. Comparison of percentage changes in quantitative diffusion parameters for assessing pathological complete response to neoadjuvant therapy in locally advanced rectal cancer: a meta-analysis. Abdom Radiol (NY) 2021;46:894-908. [PMID: 32975646 DOI: 10.1007/s00261-020-02770-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 09/02/2020] [Accepted: 09/10/2020] [Indexed: 02/01/2023]

Wu B, Jia F, Li X, Li L, Wang K, Han D. Comparative Study of Amide Proton Transfer Imaging and Intravoxel Incoherent Motion Imaging for Predicting Histologic Grade of Hepatocellular Carcinoma. Front Oncol 2020;10:562049. [PMID: 33194630 PMCID: PMC7659984 DOI: 10.3389/fonc.2020.562049] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 09/18/2020] [Indexed: 02/05/2023] Open

Abstract

Background: Preoperative grading of hepatocellular carcinoma (HCC) is an important factor associated with prognosis after liver resection. The promising prediction of the differentiation of HCC remains a challenge. The purpose of our study was to investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of HCC, compared with the intravoxel incoherent motion (IVIM) imaging.

Methods: From September 2018 to February 2020, 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on the histologic grades. Preoperative APT signal intensity (SI), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudo-diffusion coefficient (D^*), and perfusion fraction (f ) of HCC were independently measured by two radiologists. The averaged values of those parameters were compared using an analysis of variance. The Spearman rank analysis was used to compare the correlation between those imaging parameters and the histological grades. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.

Results: There were significant differences in APT SI, ADC, D, and f among the four grades of HCC (all P < 0.001). A moderate to good relationship was found between APT SI and the histologic grade of HCC (r = 0.679, P < 0.001). APT SI had an area under the ROC curve (AUC) of 0.890 (95% CI: 0.805–0.947) for differentiating low- from high-grade HCC, and the corresponding sensitivity and specificity were 85.71% and 82.05%, respectively. Comparison of ROC curves demonstrated that the AUC of APT SI was significantly higher than those of IVIM-derived parameter (Z = 2.603, P = 0.0092; Z = 2.099, P = 0.0358; Z = 4.023, P = 0.0001; Z = 2.435, P = 0.0149, compared with ADC, D, D^*, and f , respectively). Moreover, the combination of both techniques further improved the diagnostic performance, with an AUC of 0.929 (95% CI: 0.854–0.973).

Conclusion: APT imaging may be a potential noninvasive biomarker for the prediction of histologic grading of HCC and complements IVIM imaging for the more accurate and comprehensive characterization of HCC.

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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

Jia F, Wu B, Yan R, Li L, Wang K, Han D. Prediction Model for Intermediate-Stage Hepatocellular Carcinoma Response to Transarterial Chemoembolization. J Magn Reson Imaging 2020;52:1657-1667. [PMID: 32424881 DOI: 10.1002/jmri.27189] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/19/2020] [Accepted: 04/21/2020] [Indexed: 02/05/2023] Open

Abstract

BACKGROUND

The outcome of intermediate-stage hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) is greatly heterogeneous. Current means for predicting HCC response to TACE are lacking.

PURPOSE

To investigate whether the combination of parameters derived from amide proton transfer (APT) and intravoxel incoherent motion (IVIM) imaging, and morphological characteristics of tumor can establish a better prediction model than the univariant model for HCC response to TACE.

STUDY TYPE

Prospective.

SUBJECTS

56 patients with intermediate-stage HCC (50 males and six females).

FIELD STRENGTH/SEQUENCES

3.0T; T₂ -weighted-fast spin echo, 3D liver acquisition with volume flex, single-shot fast spin echo-planar imaging (EPI), spin echo-EPI.

ASSESSMENT

Pretreatment APT signal intensities (SIs), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) for tumor, peritumoral, and normal tissues were measured. Follow-up MRI scanning was performed, and the patients were classified as responders or nonresponders based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) criteria.

STATISTICAL TESTS

The imaging parameters were compared among the three tissues and between the two groups using analysis of variance (ANOVA) or two-sample t-test. The prediction model's variables were derived from univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.

RESULTS

Based on the logistic regression analysis results, we established a prediction model that integrated the APT SI and D values in the tumor tissue and the tumor size. ROC analyses revealed that the model was better able to predict tumor response to TACE (area under the ROC curve = 0.851) than the individual parameters on their own.

DATA CONCLUSION

A prediction model incorporating pretreatment APT SI, D in the tumor tissue and tumor size may be useful for predicting the response of intermediate-stage HCC to TACE.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 1 J. MAGN. RESON. IMAGING 2020;52:1657-1667.

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