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Zhang X, Wang Y, Xu X, Hu M, Wang S, Chen Y, Zhao X. Prospective Comparison of 2D and 3D T2-Weighted Imaging in Multiparametric MRI for Assessing Muscle Invasion Accuracy Using VI-RADS in Bladder Cancer. Acad Radiol 2024:S1076-6332(24)00437-9. [PMID: 39043518 DOI: 10.1016/j.acra.2024.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/24/2024] [Accepted: 07/02/2024] [Indexed: 07/25/2024]
Abstract
RATIONALE AND OBJECTIVES T2-weighted imaging (T2WI) is an essential sequence for assessing the staging of bladder cancer. This study aimed to compare the image quality and diagnostic performance of three-dimensional (3D) and two-dimensional (2D) T2WI in diagnosing muscle invasion of bladder cancer using Vesical Imaging Reporting and Data System (VI-RADS). MATERIALS AND METHODS Between August 2022 and May 2023, 101 participants with bladder cancer underwent multiparametric MRI including 3D and 2D T2WI. Two radiologists independently reviewed 2D and 3D T2WI, evaluating image quality and muscle invasion based on VI-RADS scoring. The paired Wilcoxon signed-rank test assessed the differences between 2D and 3D T2WI. The areas under the receiver operating characteristic curve (AUCs) were utilized to compare the diagnostic performance. RESULTS 3D T2WI demonstrated significantly superior overall image quality scores with less artifacts than 2D T2WI. Compared to 2D T2WI, 3D T2WI categories had significantly higher AUC for both readers (reader 1: 0.937 vs. 0.909, p = .02; reader 2: 0.923 vs.0.884, p = .04). The VI-RADS score of 3D MR protocol had higher accuracy than 2D MR protocol (reader 1: 0.931 vs. 0.921, p = .02; reader 2: 0.931 vs. 0.911, p = .02). However, there were no significant differences in AUC values of VI-RADS categories between 2D and 3D MR protocol (all p > 0.05). CONCLUSION In assessing muscle invasion of bladder cancer, 3D T2WI exhibited superior overall image quality and diagnostic performance than 2D T2WI. However, 3D T2WI did not significantly improve the diagnostic performance of VI-RADS.
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Affiliation(s)
- Xinxin Zhang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.)
| | - Yichen Wang
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.)
| | - Xiaojuan Xu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.)
| | - Mancang Hu
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.)
| | - Sicong Wang
- GE Healthcare, MR Research China, Tongji south road No1, Beijing 100176, China (S.W.)
| | - Yan Chen
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.)
| | - Xinming Zhao
- Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China (X.Z., Y.W., X.X., M.H., Y.C., X.Z.).
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Li L, Zhang J, Zhe X, Tang M, Zhang L, Lei X, Zhang X. Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI. Urol Oncol 2024; 42:176.e9-176.e20. [PMID: 38556403 DOI: 10.1016/j.urolonc.2024.02.008] [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: 09/16/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024]
Abstract
PURPOSE To compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade. MATERIALS AND METHODS This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models. RESULTS The area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model. CONCLUSION The bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.
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Affiliation(s)
- Longchao Li
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Jing Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Xia Zhe
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Min Tang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
| | - Li Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.
| | - Xiaoyan Lei
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China.
| | - Xiaoling Zhang
- Department of MRI, Shaanxi Provincial People's Hospital, Xi'an, Shaanxi, China
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Wang J, Hu S, Liang P, Hu X, Shen Y, Peng Y, Kamel I, Li Z. R2* mapping and reduced field-of-view diffusion-weighted imaging for preoperative assessment of nonenlarged lymph node metastasis in rectal cancer. NMR IN BIOMEDICINE 2024:e5174. [PMID: 38712650 DOI: 10.1002/nbm.5174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 04/18/2024] [Accepted: 04/20/2024] [Indexed: 05/08/2024]
Abstract
The aim of the current study is to investigate the diagnostic value of R2* mapping versus reduced field-of-view diffusion-weighted imaging (rDWI) of the primary lesion of rectal cancer for preoperative prediction of nonenlarged lymph node metastasis (NLNM). Eighty-one patients with pathologically confirmed rectal cancer underwent preoperative R2* mapping and rDWI sequences before total mesorectal excisions and accompanying regional lymph node dissections. Two radiologists independently performed whole-tumor measurements of R2* and apparent diffusion coefficient (ADC) parameters on primary lesions of rectal cancer. Patients were divided into positive (NLNM+) and negative (NLNM-) groups based on their pathological analysis. The tumor location, maximum diameter of the tumor, and maximum short diameter of the lymph node were assessed. R2* and ADC, pT stage, tumor grade, status of mesorectal fascia, and extramural vascular invasion were also studied for their potential relationships with NLNM using multivariate logistic regression analysis. The NLNM+ group had significantly higher R2* (43.56 ± 8.43 vs. 33.87 ± 9.57, p < 0.001) and lower ADC (1.00 ± 0.13 vs. 1.06 ± 0.22, p = 0.036) than the NLNM- group. R2* and ADC were correlated to lymph node metastasis (r = 0.510, p < 0.001 for R2*; r = -0.235, p = 0.035 for ADC). R2* and ADC showed good and moderate diagnostic abilities in the assessment of NLNM status with corresponding area-under-the-curve values of 0.795 and 0.636. R2* provided a significantly better diagnostic performance compared with ADC for the prediction of NLNM status (z = 1.962, p = 0.0498). The multivariate logistic regression analysis demonstrated that R2* was a compelling factor of lymph node metastasis (odds ratio = 56.485, 95% confidence interval: 5.759-554.013; p = 0.001). R2* mapping had significantly higher diagnostic performance than rDWI from the primary tumor of rectal cancer in the prediction of NLNM status.
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Affiliation(s)
- Jing Wang
- Department of Pediatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shan Hu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Ping Liang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuemei Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yang Peng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ihab Kamel
- Russell H. Morgan Department of Radiology and Radiological Science, the Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
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Li J, Ma Y, Yang C, Qiu G, Chen J, Tan X, Zhao Y. Radiomics analysis of R2* maps to predict early recurrence of single hepatocellular carcinoma after hepatectomy. Front Oncol 2024; 14:1277698. [PMID: 38463221 PMCID: PMC10920317 DOI: 10.3389/fonc.2024.1277698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 02/09/2024] [Indexed: 03/12/2024] Open
Abstract
Objectives This study aimed to evaluate the effectiveness of radiomics analysis with R2* maps in predicting early recurrence (ER) in single hepatocellular carcinoma (HCC) following partial hepatectomy. Methods We conducted a retrospective analysis involving 202 patients with surgically confirmed single HCC having undergone preoperative magnetic resonance imaging between 2018 and 2021 at two different institutions. 126 patients from Institution 1 were assigned to the training set, and 76 patients from Institution 2 were assigned to the validation set. A least absolute shrinkage and selection operator (LASSO) regularization was conducted to operate a logistic regression, then features were identified to construct a radiomic score (Rad-score). Uni- and multi-variable tests were used to assess the correlations of clinicopathological features and Rad-score with ER. We then established a combined model encompassing the optimal Rad-score and clinical-pathological risk factors. Additionally, we formulated and validated a predictive nomogram for predicting ER in HCC. The nomogram's discrimination, calibration, and clinical utility were thoroughly evaluated. Results Multivariable logistic regression revealed the Rad-score, microvascular invasion (MVI), and α fetoprotein (AFP) level > 400 ng/mL as significant independent predictors of ER in HCC. We constructed a nomogram based on these significant factors. The areas under the receiver operator characteristic curve of the nomogram and precision-recall curve were 0.901 and 0.753, respectively, with an F1 score of 0.831 in the training set. These values in the validation set were 0.827, 0.659, and 0.808. Conclusion The nomogram that integrates the radiomic score, MVI, and AFP demonstrates high predictive efficacy for estimating the risk of ER in HCC. It facilitates personalized risk classification and therapeutic decision-making for HCC patients.
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Affiliation(s)
- Jia Li
- Department of Oncology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Yunhui Ma
- Department of Oncology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Chunyu Yang
- Department of Radiology, The First School of Clinical Medicine, Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, China
| | - Ganbin Qiu
- Imaging Department of Zhaoqing Medical College, Zhaoqing, China
| | - Jingmu Chen
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Xiaoliang Tan
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
| | - Yue Zhao
- Department of Radiology, Central People’s Hospital of Zhanjiang, Zhanjiang, China
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5
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He K, Meng X, Wang Y, Feng C, Liu Z, Li Z, Niu Y. Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review. Diagnostics (Basel) 2024; 14:442. [PMID: 38396481 PMCID: PMC10888296 DOI: 10.3390/diagnostics14040442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/25/2024] [Accepted: 02/13/2024] [Indexed: 02/25/2024] Open
Abstract
Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.
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Affiliation(s)
- Kangwen He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Yanchun Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Zheng Liu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China (X.M.); (Z.L.)
| | - Yonghua Niu
- Department of Pediatric Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Zhou M, Huang H, Fan Y, Chen M, Li M, Wang Y. The application of quantitative perfusion analysis of golden-angle radial sparse parallel MRI and R2∗ value for predicting pathological prognostic factors in rectal cancer. Clin Radiol 2024; 79:124-132. [PMID: 38030505 DOI: 10.1016/j.crad.2023.10.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/25/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023]
Abstract
AIM To investigate the diagnostic value of golden-angle radial sparse parallel magnetic resonance imaging (MRI) (GRASP) and R2∗ in predicting the prognostic factors of resectable rectal cancer. MATERIALS AND METHODS A total of 108 patients with rectal adenocarcinoma were included in this retrospective study. The volume transfer constant (Ktrans), rate constant (Kep), plasma volume fraction (Ve), and R2∗ were obtained. Univariate and multivariate logistic regression were conducted. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of the imaging parameters. RESULTS The Ktrans was found to be significantly higher in rectal cancers with positive lymph node metastasis (LNM), higher tumour grade, positive lymphovascular invasion (LVI), and higher ki-67 (all p<0.05). The Kep was also significantly higher in the LNM-positive group (p<0.001), while the R2∗ was higher in rectal cancers with LNM-positive, higher tumour grade, LVI-positive, and higher ki-67 (all p<0.05). Combining the Ktrans and R2∗ provided the highest area under the ROC curve (AUC) for LNM-positive and higher ki-67 tumours differentiation (0.790 and 0.823, respectively). DISCUSSION Combining quantitative parameters of the Ktrans and R2∗ could be used to non-invasively predict pathological prognostic factors preoperatively.
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Affiliation(s)
- M Zhou
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - H Huang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Y Fan
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - M Chen
- Department of MR Scientific Marketing, Siemens Healthineers, Shanghai, 200135, China
| | - M Li
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China
| | - Y Wang
- Department of Radiology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, 610072, China.
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Meng X, Li S, He K, Hu H, Feng C, Li Z, Wang Y. Evaluation of Whole-Tumor Texture Analysis Based on MRI Diffusion Kurtosis and Biparametric VI-RADS Model for Staging and Grading Bladder Cancer. Bioengineering (Basel) 2023; 10:745. [PMID: 37508772 PMCID: PMC10376391 DOI: 10.3390/bioengineering10070745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/16/2023] [Accepted: 06/18/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND to evaluate the feasibility of texture analysis (TA) based on diffusion kurtosis imaging (DKI) in staging and grading bladder cancer (BC) and to compare it with apparent diffusion coefficient (ADC) and biparametric vesical imaging reporting and data system (VI-RADS). MATERIALS AND METHODS In this retrospective study, 101 patients with pathologically confirmed BC underwent MRI with multiple-b values ranging from 0 to 2000 s/mm2. ADC- and DKI-derived parameters, including mean kurtosis (MK) and mean diffusivity (MD), were obtained. First-order texture histogram parameters of MK and MD, including the mean; 5th, 25th, 50th, 75th, and 90th percentiles; inhomogeneity; skewness: kurtosis; and entropy; were extracted. The VI-RADS score was evaluated based on the T2WI and DWI. The Mann-Whitney U-test was used to compare the texture parameters and ADC values between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), as well as between low and high grades. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of each significant parameter and their combinations. RESULTS The NMIBC and low-grade group had higher MDmean, MD5th, MD25th, MD50th, MD75th, MD90th, and ADC values than those of the MIBC and the high-grade group. The NMIBC and low-grade group yielded lower MKmean, MK25th, MK50th, MK75th, and MK90th than the MIBC and high-grade group. Among all histogram parameters, MD75th and MD90th yielded the highest AUC in differentiating MIBC from NMIBC (both AUCs were 0.87), while the AUC for ADC was 0.86. The MK75th and MK90th had the highest AUC (both 0.79) in differentiating low- from high-grade BC, while ADC had an AUC of 0.68. The AUC (0.92) of the combination of DKI histogram parameters (MD75th, MD90th, and MK90th) with biparametric VI-RADS in staging BC was higher than that of the biparametric VI-RADS (0.89). CONCLUSIONS Texture-analysis-derived DKI is useful in evaluating both the staging and grading of bladder cancer; in addition, the histogram parameters of the DKI (MD75th, MD90th, and MK90th) can provide additional value to VI-RADS.
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Affiliation(s)
- Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shichao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Kangwen He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Henglong Hu
- Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yanchun Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
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Xu X, Chen M, Zhang J, Jiang Y, Chao H, Zha J. Can the apparent transverse relaxation rate (R2 *) evaluate the efficacy of concurrent chemoradiotherapy in locally advanced nasopharyngeal carcinoma? a preliminary experience. BMC Med Imaging 2023; 23:69. [PMID: 37264331 DOI: 10.1186/s12880-023-01029-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Accepted: 05/23/2023] [Indexed: 06/03/2023] Open
Abstract
BACKGROUND The use of the apparent transverse relaxation rate (R2*) in nasopharyngeal carcinoma (NPC) has not been previously reported in the literature. The aim of this study was to investigate the role of the R2* value in evaluating response to concurrent chemoradiotherapy (CCRT) in patients with NPC. METHODS Forty-one patients with locoregionally advanced NPC confirmed by pathology were examined by blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) before and after CCRT, and conventional MRI was performed 3 months after the completion of CCRT. All patients were divided into a responding group (RG) and a nonresponding group (NRG), according to MRI findings 3 months after the end of treatment. The R2* values before (R2*preT) and after (R2*postT) CCRT and the ΔR2* (ΔR2*=R2*postT - R2*preT) were calculated in the tumor. RESULTS Among the 41 patients, 26 were in the RG and 15 were in the NRG. There was no statistical difference in the R2*preT between RG and NRG (P = 0.307); however, there were significant differences in R2*postT and ΔR2* (P < 0.001). The area under the curve of R2*postT and ΔR2* for predicting the therapeutic response of NPC was 0.897 and 0.954, respectively, with cutoff values of 40.95 and 5.50 Hz, respectively. CONCLUSION The R2* value can be used as a potential imaging indicator to evaluate the therapeutic response of locoregionally advanced NPC.
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Affiliation(s)
- Xinhua Xu
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China
| | - Ming Chen
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China.
| | - Jin Zhang
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China
| | - Yunzhu Jiang
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China
| | - Hua Chao
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China
| | - Jianfeng Zha
- Department of Radiology, Changzhou Cancer Hospital of Soochow University, 68 Honghe Road, Changzhou, 213000, Jiangsu, PR China
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Zhang W, Zhang Z, Xiao W, Wang Y, Ye L, Wei Y, Luo M. Multiple directional DWI combined with T2WI in predicting muscle layer and Ki-67 correlation in bladder cancer in 3.0-T MRI. Cancer Med 2023; 12:10462-10472. [PMID: 36916547 DOI: 10.1002/cam4.5782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/16/2023] Open
Abstract
OBJECTIVE To investigate the value of 3.0T MRI multi-directional diffusion-weighted imaging (DWI) combined with T2WI morphological features and lesion distribution in preoperative prediction of muscle layer invasion of bladder cancer (BC) and the correlation with postoperative Ki-67. MATERIALS AND METHODS This retrospective study enrolled patients with BC between 2019 and 2021. Patients with muscular invasive bladder cancer (MIBC) or non-muscular invasive BC (NMIBC) were also analyzed by preoperative 3.0T MRI aFostic efficacy. RESULTS A total of 186 patients were enrolled. About 27 patients with MIBC (35 lesions in total) and 62 with NMIBC (99 lesions in total). We found the tumor with a larger size, a wide base, and a smaller apparent dispersion coefficient (ADC) value and normalized ADC(nADC) value, without a stalk, presenting a greater risk of muscle invasion. ADC value, nADC value, maximum diameter, and stalk were independently associated with muscle invasion. Lesions located at the bladder fundus or involvement of multiple sites were independently associated with muscle invasion compared to the bladder body. In combination with morphological features, the AUCs of ADC and nADC showed accuracies of 0.925 and 0.947-0.951, respectively. TADC and nTADC showed the best diagnostic efficacy in multiple respects. KI-67 LI was negatively correlated with ADC and nADC values. CONCLUSIONS This is the first report in which we found Multi-directional DWI combined with T2WI in 3.0T MRI can be used to predict the muscle layer invasion of bladder cancer. ADC values reflect the muscular invasion of bladder cancer and show a moderate negative correlation with Ki-67. It is especially suitable for bladder cancer patients with renal insufficiency or tumor recurrence.
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Affiliation(s)
- Wei Zhang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
| | - Zhichao Zhang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Medical University Cancer Hospital, Fujian Cancer Hospital, Fuzhou, China
| | - Weixiong Xiao
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
| | - Yiqian Wang
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
| | - Liefu Ye
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Urology, Fujian Provincial Hospital, Fuzhou, China
| | - Yongbao Wei
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Urology, Fujian Provincial Hospital, Fuzhou, China
| | - Min Luo
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.,Department of Radiology, Fujian Provincial Hospital, Fuzhou, China
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10
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Radiomics Nomogram Based on High-b-Value Diffusion-Weighted Imaging for Distinguishing the Grade of Bladder Cancer. Life (Basel) 2022; 12:life12101510. [DOI: 10.3390/life12101510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/03/2022] [Accepted: 09/23/2022] [Indexed: 12/24/2022] Open
Abstract
Background: The aim was to evaluate the feasibility of radiomics features based on diffusion-weighted imaging (DWI) at high b-values for grading bladder cancer and to compare the possible advantages of high-b-value DWI over the standard b-value DWI. Methods: Seventy-four participants with bladder cancer were included in this study. DWI sequences using a 3 T MRI with b-values of 1000, 1700, and 3000 s/mm2 were acquired, and the corresponding ADC maps were generated, followed with feature extraction. Patients were randomly divided into training and testing cohorts with a ratio of 8:2. The radiomics features acquired from the ADC1000, ADC1700, and ADC3000 maps were compared between low- and high-grade bladder cancers by using the Wilcox analysis, and only the radiomics features with significant differences were selected. The least absolute shrinkage and selection operator method and a logistic regression were performed for the feature selection and establishing the radiomics model. A receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of the radiomics models. Results: In the training cohorts, the AUCs of the ADC1000, ADC1700, and ADC3000 model for discriminating between low- from high-grade bladder cancer were 0.901, 0.920, and 0.901, respectively. In the testing cohorts, the AUCs of ADC1000, ADC1700, and ADC3000 were 0.582, 0.745, and 0.745, respectively. Conclusions: The radiomics features extracted from the ADC1700 maps could improve the diagnostic accuracy over those extracted from the conventional ADC1000 maps.
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11
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Hu S, Peng Y, Wang Q, Liu B, Kamel I, Liu Z, Liang C. T2*-weighted imaging and diffusion kurtosis imaging (DKI) of rectal cancer: correlation with clinical histopathologic prognostic factors. Abdom Radiol (NY) 2022; 47:517-529. [PMID: 34958406 DOI: 10.1007/s00261-021-03369-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 11/26/2021] [Accepted: 11/27/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE Histopathologic prognostic factors of rectal cancer are closely associated with local recurrence and distant metastasis. We aim to investigate the feasibility of T2*WI in assessment of clinical prognostic factors of rectal cancer, and compare with DKI. METHODS This retrospective study enrolled 50 out of 205 patients with rectal cancer according to the inclusion criteria. The following parameters were obtained: R2* from T2*WI, mean diffusivity (MDk), mean kurtosis (MK), and mean diffusivity (MDt) from DKI using tensor method. Above parameters were compared by Mann-Whitney U-test or students' t test. Spearman correlations between different parameters and histopathological prognostic factors were determined. The diagnostic performances of R2* and DKI-derived parameters were analyzed by receiver operating characteristic curves (ROC), separately and jointly. RESULTS There were positive correlations between R2* and multiple prognostic factors of rectal cancer such as T category, N category, tumor grade, CEA level, and LVI (P < 0.004). MDk and MDt showed negative correlations with almost all the histopathological prognostic factors except CRM and TIL involvement (P < 0.003). MK correlated positively with the prognostic factors except CA19-9 level and CRM involvement (P < 0.006). The AUC ranges were 0.724-0.950 for R2* and 0.755-0.913 for DKI-derived parameters for differentiation of prognostic factors. However, no significant differences of diagnostic performance were found between T2*WI, DKI, or the combined imaging methods in characterizing rectal cancer. CONCLUSION R2* and DKI-derived parameters were associated with different histopathological prognostic factors, and might act as noninvasive biomarkers for histopathological characterization of rectal cancer.
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12
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Apparent Diffusion Coefficient Value as a Biomarker for Detecting Muscle-Invasive and High-Grade Bladder Cancer: A Systematic Review. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12031278] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: Several studies have investigated the potential role of the apparent diffusion coefficient (ADC) value of diffusion-weighted magnetic resonance imaging as a biomarker of high-grade and invasive bladder cancer. Methods: PubMed and the Cochrane Library were systematically searched in September 2021 to extract studies that evaluated the associations between ADC values, pathological T stage, and histological grade bladder cancers. The diagnostic performance of ADC values in detecting muscle-invasive bladder cancer (MIBC) and high-grade disease was systematically reviewed. Results: Six studies were included in this systematic review. MIBC showed significantly lower ADC values than non-muscle-invasive bladder cancer (NMIBC) in all six studies. The median (range) sensitivity, specificity, and area under the curve (AUC) of ADC values to detect MIBC among the four eligible studies were 73.5% (68.8–90.0%), 79.9% (66.7–84.4%), and 0.762 (0.730–0.884), respectively. Similarly, high-grade disease showed significantly lower ADC values than did low-grade disease in all four eligible studies. The median (range) sensitivity, specificity, and AUC of ADC values for detecting high-grade disease among the three eligible studies were 75.0% (73.0–76.5%), 95.8% (76.2–100%), and 0.902 (0.804–0.906), respectively. Conclusions: The ADC value is a non-invasive diagnostic biomarker for discriminating muscle-invasive and high-grade bladder cancer.
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13
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Feng C, Wang Y, Dan G, Zhong Z, Karaman MM, Li Z, Hu D, Zhou XJ. Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma. Eur Radiol 2021; 32:890-900. [PMID: 34342693 DOI: 10.1007/s00330-021-08203-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/30/2021] [Accepted: 06/30/2021] [Indexed: 12/24/2022]
Abstract
OBJECTIVES To evaluate the feasibility of high b-value diffusion-weighted imaging (DWI) for distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC) and low- from high-grade bladder urothelial carcinoma using a fractional-order calculus (FROC) model as well as a combination of FROC DWI and bi-parametric Vesical Imaging-Reporting and Data System (VI-RADS). METHODS Fifty-eight participants with bladder urothelial carcinoma were included in this IRB-approved prospective study. Diffusion-weighted images, acquired with 16 b-values (0-3600 s/mm2), were analyzed using the FROC model. Three FROC parameters, D, β, and μ, were used for delineating NMIBC from MIBC and for tumor grading. A receiver operating characteristic (ROC) analysis was performed based on the individual FROC parameters and their combinations, followed by comparisons with apparent diffusion coefficient (ADC) and bi-parametric VI-RADS based on T2-weighted images and DWI. RESULTS D and μ were significantly lower in the MIBC group than in the NMIBC group (p = 0.001 for each), and D, β, and μ all exhibited significantly lower values in the high- than in the low-grade tumors (p ≤ 0.011). The combination of D, β, and μ produced the highest specificity (85%), accuracy (78%), and the area under the ROC curve (AUC, 0.782) for distinguishing NMIBC and MIBC, and the best sensitivity (89%), specificity (86%), accuracy (88%), and AUC (0.892) for tumor grading, all of which outperformed the ADC. The combination of FROC parameters with bi-parametric VI-RADS improved the AUC from 0.859 to 0.931. CONCLUSIONS High b-value DWI with a FROC model is useful in distinguishing NMIBC from MIBC and grading bladder tumors. KEY POINTS • Diffusion parameters derived from a FROC diffusion model may differentiate NMIBC from MIBC and low- from high-grade bladder urothelial carcinomas. • Under the condition of a moderate sample size, higher AUCs were achieved by the FROC parameters D (0.842) and μ (0.857) than ADC (0.804) for bladder tumor grading with p ≤ 0.046. • The combination of the three diffusion parameters from the FROC model can improve the specificity over ADC (85% versus 67%, p = 0.031) for distinguishing NMIBC and MIBC and enhance the performance of bi-parametric VI-RADS.
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Affiliation(s)
- Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou District, Wuhan, 430030, China.,Center for MR Research, University of Illinois at Chicago, MC-707, Suite 1A, 1801 West Taylor Street, Chicago, IL, 60612, USA
| | - Yanchun Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou District, Wuhan, 430030, China
| | - Guangyu Dan
- Center for MR Research, University of Illinois at Chicago, MC-707, Suite 1A, 1801 West Taylor Street, Chicago, IL, 60612, USA.,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Zheng Zhong
- Center for MR Research, University of Illinois at Chicago, MC-707, Suite 1A, 1801 West Taylor Street, Chicago, IL, 60612, USA.,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - M Muge Karaman
- Center for MR Research, University of Illinois at Chicago, MC-707, Suite 1A, 1801 West Taylor Street, Chicago, IL, 60612, USA.,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou District, Wuhan, 430030, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Qiaokou District, Wuhan, 430030, China.
| | - Xiaohong Joe Zhou
- Center for MR Research, University of Illinois at Chicago, MC-707, Suite 1A, 1801 West Taylor Street, Chicago, IL, 60612, USA. .,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA. .,Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA. .,Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA.
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14
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Xu X, Wang H, Guo Y, Zhang X, Li B, Du P, Liu Y, Lu H. Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer. Front Oncol 2021; 11:704039. [PMID: 34336691 PMCID: PMC8321511 DOI: 10.3389/fonc.2021.704039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Accepted: 06/30/2021] [Indexed: 12/24/2022] Open
Abstract
Urinary bladder cancer (BCa) is a highly prevalent disease among aged males. Precise diagnosis of tumor phenotypes and recurrence risk is of vital importance in the clinical management of BCa. Although imaging modalities such as CT and multiparametric MRI have played an essential role in the noninvasive diagnosis and prognosis of BCa, radiomics has also shown great potential in the precise diagnosis of BCa and preoperative prediction of the recurrence risk. Radiomics-empowered image interpretation can amplify the differences in tumor heterogeneity between different phenotypes, i.e., high-grade vs. low-grade, early-stage vs. advanced-stage, and nonmuscle-invasive vs. muscle-invasive. With a multimodal radiomics strategy, the recurrence risk of BCa can be preoperatively predicted, providing critical information for the clinical decision making. We thus reviewed the rapid progress in the field of medical imaging empowered by the radiomics for decoding the phenotype and recurrence risk of BCa during the past 20 years, summarizing the entire pipeline of the radiomics strategy for the definition of BCa phenotype and recurrence risk including region of interest definition, radiomics feature extraction, tumor phenotype prediction and recurrence risk stratification. We particularly focus on current pitfalls, challenges and opportunities to promote massive clinical applications of radiomics pipeline in the near future.
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Affiliation(s)
- Xiaopan Xu
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Huanjun Wang
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yan Guo
- Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Xi Zhang
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Baojuan Li
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Peng Du
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Yang Liu
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
| | - Hongbing Lu
- School of Biomedical Engineering, Air Force Medical University, Xi’an, China
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15
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Cai Q, Wen Z, Huang Y, Li M, Ouyang L, Ling J, Qian L, Guo Y, Wang H. Investigation of Synthetic Magnetic Resonance Imaging Applied in the Evaluation of the Tumor Grade of Bladder Cancer. J Magn Reson Imaging 2021; 54:1989-1997. [PMID: 34080268 DOI: 10.1002/jmri.27770] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 05/23/2021] [Accepted: 05/24/2021] [Indexed: 12/16/2022] Open
Affiliation(s)
- Qian Cai
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Zhihua Wen
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Yiping Huang
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Meiqin Li
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Longyuan Ouyang
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Jian Ling
- Department of Radiology The Eastern Hospital of the First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Long Qian
- MR Research, GE Healthcare Beijing China
| | - Yan Guo
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
| | - Huanjun Wang
- Department of Radiology The First Affiliated Hospital, Sun Yat‐Sen University Guangzhou Guangdong China
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16
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Peng Y, Luo Y, Hu X, Shen Y, Hu D, Li Z, Kamel I. Quantitative T2*-Weighted Imaging and Reduced Field-of-View Diffusion-Weighted Imaging of Rectal Cancer: Correlation of R2* and Apparent Diffusion Coefficient With Histopathological Prognostic Factors. Front Oncol 2021; 11:670156. [PMID: 34109120 PMCID: PMC8180870 DOI: 10.3389/fonc.2021.670156] [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: 02/20/2021] [Accepted: 04/28/2021] [Indexed: 12/24/2022] Open
Abstract
Purpose To assess T2*-weighted imaging (T2*WI) and reduced field-of-view diffusion-weighted Imaging (rDWI) derived parameters and their relationships with histopathological factors in patients with rectal cancer. Methods Fifty-four patients with pathologically-proven rectal cancer underwent preoperative T2*-weighted imaging and rDWI in this retrospective study. R2* values from T2*-weighted imaging and apparent diffusion coefficient (ADC) values from rDWI were compared in terms of different histopathological prognostic factors using student’s t-test or Mann-Whitney U-test. The correlations of R2* and ADC with prognostic factors were assessed by Spearman correlation analysis. The diagnostic performances of R2* and ADC were analyzed by receiver operating characteristic curves (ROC) separately and jointly. Results Significant positive correlation was found between R2* values and T stage, lymph node involvement, histological grades, CEA level, the presence of EMVI and tumor deposit (r = 0.374 ~ 0.673, p = 0.000–0.006), with the exception of CA19-9 level, CRM status and tumor involvement in the circumference lumen (TIL). Meanwhile, ADC values negatively correlated with almost all the prognostic factors (r = −0.588 to −0.299, p = 0.000–0.030), except CA19-9 level. The AUC range was 0.724–0.907 for R2* and 0.674–0.887 for ADC in discrimination of different prognostic factors. While showing the highest AUC of 0.913 (0.803–1.000) in differentiation of T stage, combination of R2* and ADC with reference to different prognostic factors did not significantly improve the diagnostic performance in comparison with individual R2*/ADC parameter. Conclusions R2* and ADC were associated with important histopathological prognostic factors of rectal cancer. R2* might act as additional quantitative imaging marker for tumor characterization of rectal cancer.
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Affiliation(s)
- Yang Peng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Luo
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xuemei Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yaqi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Daoyu Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhen Li
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ihab Kamel
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States
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17
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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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Affiliation(s)
- Guang-Zi Shi
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Hong Chen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Wei-Ke Zeng
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Ming Gao
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
| | - Meng-Zhu Wang
- MR Scientific Marketing, Siemens Healthineers, Guangzhou 510120, Guangdong Province, China
| | - Hui-Ting Zhang
- MR Scientific Marketing, Siemens Healthineers, Guangzhou 510120, Guangdong Province, China
| | - Jun Shen
- Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
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