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Bai B, Cui L, Chu F, Wang Z, Zhao K, Wang S, Wang S, Yan X, Wang M, Kamel IR, Yang G, Qu J. Multiple diffusion models for predicting pathologic response of esophageal squamous cell carcinoma to neoadjuvant chemotherapy. Abdom Radiol (NY) 2024:10.1007/s00261-024-04474-7. [PMID: 38954001 DOI: 10.1007/s00261-024-04474-7] [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: 03/18/2024] [Revised: 06/22/2024] [Accepted: 06/24/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND To assess the feasibility and diagnostic performance of the fractional order calculus (FROC), continuous-time random-walk (CTRW), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM), mono-exponential (MEM) and stretched exponential models (SEM) for predicting response to neoadjuvant chemotherapy (NACT) in patients with esophageal squamous cell carcinoma (ESCC). MATERIALS AND METHODS This study prospectively included consecutive ESCC patients with baseline and follow up MR imaging and pathologically confirmed cT1-4aN + M0 or T3-4aN0M0 and underwent radical resection after neoadjuvant chemotherapy (NACT) between July 2019 and January 2023. Patients were divided into pCR (TRG 0) and non-pCR (TRG1 + 2 + 3) groups according to tumor regression grading (TRG). The Pre-, Post- and Delta-treatment models were built. 18 predictive models were generated according to different feature categories, based on six models by five-fold cross-validation. Areas under the curve (AUCs) of the models were compared by using DeLong method. RESULTS Overall, 90 patients (71 men, 19 women; mean age, 64 years ± 6 [SD]) received NACT and underwent baseline and Post-NACT esophageal MRI, with 29 patients in the pCR group and 61 patients in the non-pCR group. Among 18 predictive models, The Pre-, Post-, and Delta-CTRW model showed good predictive efficacy (AUC = 0.722, 0.833 and 0.790). Additionally, the Post-FROC model (AUC = 0.907) also exhibited good diagnostic performance. CONCLUSIONS Our study indicates that the CTRW model, along with the Post-FROC model, holds significant promise for the future of NACT efficacy prediction in ESCC patients.
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Affiliation(s)
- Bingmei Bai
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Long Cui
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Funing Chu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Zhaoqi Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Keke Zhao
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shuting Wang
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China
| | - Shaoyu Wang
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Xu Yan
- MR Scientific Marketing, Siemens Healthineers, Shanghai, 201318, China
| | - Mengzhu Wang
- MR Research Collaboration, Siemens Healthineers Ltd, Beijing, 100000, China
| | - Ihab R Kamel
- Department of Radiology, Anschutz Medical Campus, University of Colorado Denver, 12401 East 17Th Avenue, Aurora, CO, 80045, USA
| | - Guang Yang
- Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, 200062, China
| | - Jinrong Qu
- Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, China.
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Mohamed YAE, Abdelghaffar MM, Khalaf SS, Amin AF, Mostafa MA, Harb O, Mohamed AH, Abdelfattah AR. Gastrointestinal stromal tumor of the duodenum presenting with shock and massive upper and lower gastrointestinal bleeding: a case report and review of the literature. J Med Case Rep 2024; 18:286. [PMID: 38907357 PMCID: PMC11193304 DOI: 10.1186/s13256-024-04597-x] [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: 02/21/2024] [Accepted: 05/19/2024] [Indexed: 06/23/2024] Open
Abstract
BACKGROUND Due to rarity of duodenal GISTs, clinicians have few information about its clinical features, diagnosis, management and prognosis. CASE REPORT We report a case of promptly diagnosed duodenal GIST in a 61-year-old Egyptian man presented shocked with severe attack of hematemesis and melena. Upper gastroduodenal endoscopy was done and revealed a large ulcerating bleeding mass at first part of duodenum 4 hemo-clips were applied with good hemostasis. An exploratory laparotomy and distal gastrectomy, duodenectomy and gastrojejunostomy were performed. The morphology of the mass combined with immunohistochemistry was consistent with duodenal gastrointestinal stromal tumours (GISTs) of high risk type. The patient is on amatinib one tablet daily and he was well with no evidence of tumor recurrence. CONCLUSION despite being rare, emergency presentation with sudden severe, life-threatening hemorrhagic shock duodenal GISTs might be a cause of potentially lethal massive combined upper and lower gastrointestinal bleeding which is the key feature of this rare and challenging tumor.
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Affiliation(s)
| | | | - Samar S Khalaf
- Department of Biochemistry, Faculty of Pharmacy, Heliopolis University, Cairo, Egypt
| | - Ahmed F Amin
- Department of Anesthesia and ICU, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Mostafa Adel Mostafa
- Department of Anesthesia and ICU, Faculty of Medicine, Zagazig University, Zagazig, Egypt
| | - Ola Harb
- Department of Pathology, Faculty of Medicine, Zagazig Universit, Zagazig, Egypt.
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Tang C, Li F, He L, Hu Q, Qin Y, Yan X, Ai T. Comparison of continuous-time random walk and fractional order calculus models in characterizing breast lesions using histogram analysis. Magn Reson Imaging 2024; 108:47-58. [PMID: 38307375 DOI: 10.1016/j.mri.2024.01.012] [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: 08/11/2023] [Revised: 11/11/2023] [Accepted: 01/22/2024] [Indexed: 02/04/2024]
Abstract
OBJECTIVE To compare the diagnostic performance of different mathematical models for DWI and explore whether parameters reflecting spatial and temporal heterogeneity can demonstrate better diagnostic accuracy than the diffusion coefficient parameter in distinguishing benign and malignant breast lesions, using whole-tumor histogram analysis. METHODS This retrospective study was approved by the institutional ethics committee and included 104 malignant and 42 benign cases. All patients underwent breast magnetic resonance imaging (MRI) with a 3.0 T MR scanner using the simultaneous multi-slice (SMS) readout-segment ed echo-planar imaging (rs-EPI). Histogram metrics of Mono- apparent diffusion coefficient (ADC), CTRW, and FROC-derived parameters were compared between benign and malignant breast lesions, and the diagnostic performance of each diffusion parameter was evaluated. Statistical analysis was performed using Mann-Whitney U test and receiver operating characteristic (ROC) curve. RESULTS The DFROC-median exhibited the highest AUC for distinguishing benign and malignant breast lesions (AUC = 0.965). The temporal heterogeneity parameter αCTRW-median generated a statistically higher AUC compared to the spatial heterogeneity parameter βCTRW-median (AUC = 0.850 and 0.741, respectively; p = 0.047). Finally, the combination of median values of CTRW parameters displayed a slightly higher AUC than that of FROC parameters, with no significant difference however (AUC = 0.971 and 0.965, respectively; p = 0.172). CONCLUSIONS The diffusion coefficient parameter exhibited superior diagnostic performance in distinguishing breast lesions when compared to the temporal and spatial heterogeneity parameters.
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Affiliation(s)
- Caili Tang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Feng Li
- Department of Radiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei 441021, China
| | - Litong He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qilan Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yanjin Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xu Yan
- MR Research Collaboration Team, Siemens Healthineers Ltd, 278, Zhouzhu Road, Nanhui, Shanghai 201318, China
| | - Tao Ai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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Guo R, Lu F, Lin J, Fu C, Liu M, Yang S. Multi-b-value DWI to evaluate the synergistic antiproliferation and anti-heterogeneity effects of bufalin plus sorafenib in an orthotopic HCC model. Eur Radiol Exp 2024; 8:43. [PMID: 38467904 PMCID: PMC10928042 DOI: 10.1186/s41747-024-00448-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 02/06/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed synergistic effects of bufalin+sorafenib in orthotopic HCC-LM3 xenograft nude mice by using intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), a stretched exponential model (SEM), and a fractional-order calculus (FROC) model. METHODS Twenty-four orthotopic HCC-LM3 xenograft mice were divided into bufalin+sorafenib, bufalin, sorafenib treatment groups, and a control group. Multi-b-value DWI was performed using a 3-T scanner after 3 weeks' treatment to obtain true diffusion coefficient Dt, pseudo-diffusion coefficient Dp, perfusion fraction f, mean diffusivity (MD), mean kurtosis (MK), distributed diffusion coefficient (DDC), heterogeneity index α, diffusion coefficient D, fractional order parameter β, and microstructural quantity μ. Necrotic fraction (NF), standard deviation (SD) of hematoxylin-eosin staining, and microvessel density (MVD) of anti-CD31 staining were evaluated. Correlations of DWI parameters with histopathological results were analyzed, and measurements were compared among four groups. RESULTS In the final 22 mice, f positively correlated with MVD (r = 0.679, p = 0.001). Significantly good correlations of MK (r = 0.677), α (r = -0.696), and β (r= -0.639) with SD were observed (all p < 0.010). f, MK, MVD, and SD were much lower, while MD, α, β, and NF were higher in bufalin plus sorafenib group than control group (all p < 0.050). CONCLUSION Evaluated by IVIM, DKI, SEM, and FROC, bufalin+sorafenib was found to inhibit tumor proliferation and angiogenesis and reduce spatial heterogeneity in HCC-LM3 models. RELEVANCE STATEMENT Multi-b-value DWI provides potential metrics for evaluating the efficacy of treatment in HCC. KEY POINTS • Bufalin plus sorafenib combination may increase the effectiveness of HCC therapy. • Multi-b-value DWI depicted HCC proliferation, angiogenesis, and spatial heterogeneity. • Multi-b-value DWI may be a noninvasive method to assess HCC therapeutic efficacy.
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Affiliation(s)
- Ran Guo
- Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhi-jiang Road, Shanghai, 200071, People's Republic of China
| | - Fang Lu
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Jiang Lin
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People's Republic of China
- Shanghai Institute of Medical Imaging, Shanghai, 200032, People's Republic of China
| | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, 518057, People's Republic of China
| | - Mengxiao Liu
- MR scientific Marketing, Diagnostic Imaging, Siemens Healthineers Ltd, Shanghai, 201318, People's Republic of China
| | - Shuohui Yang
- Department of Radiology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhi-jiang Road, Shanghai, 200071, People's Republic of China.
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Zhong Z, Ryu K, Mao J, Sun K, Dan G, Vasanawala SS, Zhou XJ. Accelerating High b-Value Diffusion-Weighted MRI Using a Convolutional Recurrent Neural Network (CRNN-DWI). Bioengineering (Basel) 2023; 10:864. [PMID: 37508891 PMCID: PMC10376839 DOI: 10.3390/bioengineering10070864] [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: 05/11/2023] [Revised: 07/05/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
PURPOSE To develop a novel convolutional recurrent neural network (CRNN-DWI) and apply it to reconstruct a highly undersampled (up to six-fold) multi-b-value, multi-direction diffusion-weighted imaging (DWI) dataset. METHODS A deep neural network that combines a convolutional neural network (CNN) and recurrent neural network (RNN) was first developed by using a set of diffusion images as input. The network was then used to reconstruct a DWI dataset consisting of 14 b-values, each with three diffusion directions. For comparison, the dataset was also reconstructed with zero-padding and 3D-CNN. The experiments were performed with undersampling rates (R) of 4 and 6. Standard image quality metrics (SSIM and PSNR) were employed to provide quantitative assessments of the reconstructed image quality. Additionally, an advanced non-Gaussian diffusion model was employed to fit the reconstructed images from the different approaches, thereby generating a set of diffusion parameter maps. These diffusion parameter maps from the different approaches were then compared using SSIM as a metric. RESULTS Both the reconstructed diffusion images and diffusion parameter maps from CRNN-DWI were better than those from zero-padding or 3D-CNN. Specifically, the average SSIM and PSNR of CRNN-DWI were 0.750 ± 0.016 and 28.32 ± 0.69 (R = 4), and 0.675 ± 0.023 and 24.16 ± 0.77 (R = 6), respectively, both of which were substantially higher than those of zero-padding or 3D-CNN reconstructions. The diffusion parameter maps from CRNN-DWI also yielded higher SSIM values for R = 4 (>0.8) and for R = 6 (>0.7) than the other two approaches (for R = 4, <0.7, and for R = 6, <0.65). CONCLUSIONS CRNN-DWI is a viable approach for reconstructing highly undersampled DWI data, providing opportunities to reduce the data acquisition burden.
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Affiliation(s)
- Zheng Zhong
- Departments of Radiology, Stanford University, Stanford, CA 94305, USA
- Center for Magnetic Resonance Research, Chicago, IL 60612, USA
| | - Kanghyun Ryu
- Departments of Radiology, Stanford University, Stanford, CA 94305, USA
| | - Jonathan Mao
- Henry M. Gunn High School, Palo Alto, CA 94306, USA
| | - Kaibao Sun
- Center for Magnetic Resonance Research, Chicago, IL 60612, USA
| | - Guangyu Dan
- Center for Magnetic Resonance Research, Chicago, IL 60612, USA
| | | | - Xiaohong Joe Zhou
- Center for Magnetic Resonance Research, Chicago, IL 60612, USA
- Department of Radiology, Neurosurgery and Biomedical Engineering, University of Illinois Chicago, Chicago, IL 60607, USA
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Qi LP, Zhong Z, Sun YS, Li XT, Tang L, Zhou XJ. Optimal selection of b-values for differential diagnosis of mediastinal lymph nodes using diffusion-weighted imaging. Heliyon 2023; 9:e16702. [PMID: 37484276 PMCID: PMC10360569 DOI: 10.1016/j.heliyon.2023.e16702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 04/16/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023] Open
Abstract
This study proposed to investigate the optimal selection of b-values in diffusion-weighted imaging for distinguishing malignant from benign mediastinal lymph nodes. Diffusion-weighted imaging with six b-values was performed on 35 patients at 1.5 T. Image quality score, signal-to-noise ratio, and relative contrast ratio of lymph node to chest muscle were compared between the diffusion-weighted images with a b-value up to 800 and 1000 s/mm2. Using a lower and an upper b-value in the range of 0-1000 s/mm2, eight apparent diffusion coefficient maps were obtained from a mono-exponential model. Receiver operating characteristic analysis was employed to evaluate the performance of the apparent diffusion coefficients for distinguishing malignant from benign mediastinal lymph nodes by using the area under the curve as a criterion. The mean image quality score and the relative contrast ratio showed no difference between b-values of 800 and 1000 s/mm2. In the receiver operating characteristic analysis, the areas under the curve of apparent diffusion coefficient with b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm2 were significantly higher than those from the other b-value pairs. No significant difference was observed among the three b-value pairs. Apparent diffusion coefficient obtained from b-value pairs of (0, 800), (0, 1000), and (50, 800) s/mm2 showed superior diagnostic performance compared to the other b-value combinations. Based on several practical considerations, the b-value pair of (50, 800) s/mm2 is recommended for differential diagnosis of mediastinal lymph nodes.
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Affiliation(s)
- Li-Ping Qi
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Zheng Zhong
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biomedcial Engineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Ying-Shi Sun
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiao-Ting Li
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China
| | - Lei Tang
- Department of Radiology, Key Laboratory of Carcinogenesis and Translational Research, Ministry of Education, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiaohong Joe Zhou
- Center for Magnetic Resonance Research, 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
- Department of Biomedcial Engineering, University of Illinois at Chicago, Chicago, IL, USA
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Mehta R, Bu Y, Zhong Z, Dan G, Zhong PS, Zhou C, Hu W, Zhou XJ, Xu M, Wang S, Karaman MM. Characterization of breast lesions using multi-parametric diffusion MRI and machine learning. Phys Med Biol 2023; 68:085006. [PMID: 36808921 DOI: 10.1088/1361-6560/acbde0] [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: 10/13/2022] [Accepted: 02/21/2023] [Indexed: 02/23/2023]
Abstract
Objective. To investigate quantitative imaging markers based on parameters from two diffusion-weighted imaging (DWI) models, continuous-time random-walk (CTRW) and intravoxel incoherent motion (IVIM) models, for characterizing malignant and benign breast lesions by using a machine learning algorithm.Approach. With IRB approval, 40 women with histologically confirmed breast lesions (16 benign, 24 malignant) underwent DWI with 11b-values (50 to 3000 s/mm2) at 3T. Three CTRW parameters,Dm,α, andβand three IVIM parametersDdiff,Dperf, andfwere estimated from the lesions. A histogram was generated and histogram features of skewness, variance, mean, median, interquartile range; and the value of the 10%, 25% and 75% quantiles were extracted for each parameter from the regions-of-interest. Iterative feature selection was performed using the Boruta algorithm that uses the Benjamin Hochberg False Discover Rate to first determine significant features and then to apply the Bonferroni correction to further control for false positives across multiple comparisons during the iterative procedure. Predictive performance of the significant features was evaluated using Support Vector Machine, Random Forest, Naïve Bayes, Gradient Boosted Classifier (GB), Decision Trees, AdaBoost and Gaussian Process machine learning classifiers.Main Results. The 75% quantile, and median ofDm; 75% quantile off;mean, median, and skewness ofβ;kurtosis ofDperf; and 75% quantile ofDdiffwere the most significant features. The GB differentiated malignant and benign lesions with an accuracy of 0.833, an area-under-the-curve of 0.942, and an F1 score of 0.87 providing the best statistical performance (p-value < 0.05) compared to the other classifiers.Significance. Our study has demonstrated that GB with a set of histogram features from the CTRW and IVIM model parameters can effectively differentiate malignant and benign breast lesions.
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Affiliation(s)
- Rahul Mehta
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Yangyang Bu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Zheng Zhong
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Guangyu Dan
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Ping-Shou Zhong
- Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Changyu Zhou
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Weihong Hu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Xiaohong Joe Zhou
- Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Maosheng Xu
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - Shiwei Wang
- The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
- Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, People's Republic of China
| | - M Muge Karaman
- Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States of America
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States of America
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Bai JW, Qiu SQ, Zhang GJ. Molecular and functional imaging in cancer-targeted therapy: current applications and future directions. Signal Transduct Target Ther 2023; 8:89. [PMID: 36849435 PMCID: PMC9971190 DOI: 10.1038/s41392-023-01366-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 01/19/2023] [Accepted: 02/14/2023] [Indexed: 03/01/2023] Open
Abstract
Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.
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Affiliation(s)
- Jing-Wen Bai
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Department of Medical Oncology, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China
| | - Si-Qi Qiu
- Diagnosis and Treatment Center of Breast Diseases, Clinical Research Center, Shantou Central Hospital, 515041, Shantou, China
- Guangdong Provincial Key Laboratory for Breast Cancer Diagnosis and Treatment, Shantou University Medical College, 515041, Shantou, China
| | - Guo-Jun Zhang
- Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Department of Breast-Thyroid-Surgery and Cancer Center, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
- Cancer Research Center of Xiamen University, School of Medicine, Xiamen University, 361100, Xiamen, China.
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Zhaojun X, Xiaobin C, Pengfei L, Junli M, Chengwu Z, Chen L, Xiaoming M. Analysis of risk factors and prognostic factors for gastrointestinal stromal tumors with gastrointestinal hemorrhage: Based on propensity score matching method. Surgery 2023; 173:383-391. [PMID: 36424199 DOI: 10.1016/j.surg.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 10/01/2022] [Accepted: 10/03/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND This study aimed to analyze the relationship between risk factors and prognosis of patients with gastrointestinal stromal tumor associated with gastrointestinal bleeding. METHODS According to whether there was gastrointestinal bleeding, 246 patients with gastrointestinal stromal tumors were divided into 2 groups. The clinicopathological baseline characteristics of the 2 groups of patients were balanced by propensity score matching, and the Kaplan-Meier method was used to draw the survival curve and analyze the overall survival of the 2 groups of patients. The receiver operating characteristic curve was drawn to evaluate the accuracy of Modified National Institutes of Health criteria and Armed Forces Institute of Pathology criteria in predicting the prognosis and postoperative recurrence of patients. Logistic regression analysis of risk factors affecting gastrointestinal stromal tumor with gastrointestinal bleeding before matching. Univariate and multivariate analyses of risk factors affecting the prognosis of patients with gastrointestinal stromal tumors after matching were performed using Cox regression models. RESULTS Before matching, the accuracy of Modified National Institutes of Health criteria in predicting postoperative survival status and recurrence was higher than that of Armed Forces Institute of Pathology criteria. Modified National Institutes of Health criteria and relapse were the risk factors for gastrointestinal stromal tumor with gastrointestinal bleeding independent risk factors (P < .05). After 1:1 matching, the general clinical data of patients with gastrointestinal bleeding group and nongastrointestinal bleeding group were balanced (P > .05). The results of matched survival analysis indicated that tumor location and gastrointestinal bleeding were independent risk factors for the prognosis of patients with gastrointestinal stromal tumors (P < .05). The results of subgroup analysis according to anatomical site showed that there was no significant difference between the gastrointestinal bleeding group and the nongastrointestinal bleeding group (P > .05). Survival analysis showed that patients with gastrointestinal stromal tumors with gastrointestinal bleeding had a worse prognosis, and the results were also applicable in different tumor anatomical locations and different Modified National Institutes of Health criteria. CONCLUSION Modified National Institutes of Health criteria and relapse are independent risk factors for gastrointestinal stromal tumors with gastrointestinal bleeding; gastrointestinal bleeding is associated with poor prognosis in patients with gastrointestinal stromal tumors, and patients with gastrointestinal stromal tumors with gastrointestinal bleeding have a worse prognosis.
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Affiliation(s)
- Xu Zhaojun
- Graduate School, Qinghai University, Xining, China; Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai, China
| | - Chen Xiaobin
- Department of General Surgery, 900th Hospital of Joint Logistics Support Force, Fuzhou, China; Dongfang Hospital, Xiamen University, Fuzhou, China; Fuzong Clinical Medical College, Fujian Medical University, Fuzhou, China
| | - Li Pengfei
- Graduate School, Qinghai University, Xining, China; Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai, China
| | - Mi Junli
- Graduate School, Qinghai University, Xining, China; Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai, China
| | - Zhang Chengwu
- Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai, China
| | - Lin Chen
- Department of General Surgery, 900th Hospital of Joint Logistics Support Force, Fuzhou, China; Dongfang Hospital, Xiamen University, Fuzhou, China; Fuzong Clinical Medical College, Fujian Medical University, Fuzhou, China.
| | - Ma Xiaoming
- Department of Gastrointestinal Surgery, Affiliated Hospital of Qinghai University, Xining, Qinghai, China.
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Preoperative assessment of microvascular invasion of hepatocellular carcinoma using non-Gaussian diffusion-weighted imaging with a fractional order calculus model: A pilot study. Magn Reson Imaging 2023; 95:110-117. [PMID: 34506910 DOI: 10.1016/j.mri.2021.09.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 09/05/2021] [Accepted: 09/05/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE To assess the clinical potential of a set of new diffusion parameters (D, β, and μ) derived from fractional order calculus (FROC) diffusion model in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC). MATERIALS AND METHODS Between January 2019 to November 2020, a total of 63 patients with HCC were enrolled in this study. Diffusion-weighted images were acquired by using ten b-values (0-2000 s/mm2). The FROC model parameters including diffusion coefficient (D), fractional order parameter (β), a microstructural quantity (μ) together with a conventional apparent diffusion coefficient (ADC) were calculated. Intraclass coefficients were calculated for assessing the agreement of parameters quantified by two radiologists. The differences of these values between the MVI-positive and MVI-negative HCC groups were compared by using independent sample t-test or the Mann-Whitney U test. Then the parameters showing significant differences between subgroups, including the β and D, were integrated to develop a comprehensive predictive model via binary logistic regression. The diagnostic performance was evaluated by receiver operating characteristic (ROC) analysis. RESULTS Among all the studied diffusion parameters, significant differences were found in D, β, and ADC between the MVI-positive and MVI-negative groups. MVI-positive HCCs showed significantly higher β values (0.65 ± 0.17 vs. 0.51 ± 0.13, P = 0.001), along with lower D values (0.84 ± 0.11 μm2/ms vs. 1.03 ± 0.13 μm2/ms, P < 0.001) and lower ADC values (1.38 ± 0.46 μm2/ms vs. 2.09 ± 0.70 μm2/ms, P < 0.001) than those of MVI-negative HCCs. According to the ROC analysis, the combination of D and β demonstrated the largest area under the ROC curve (0.920) compared with individual parameters (D: 0.912; β: 0.733; and ADC: 0.831) for differentiating MVI-positive from MVI-negative HCCs. CONCLUSIONS The FROC parameters can be used as noninvasive quantitative imaging markers for preoperatively predicting the MVI status of HCCs.
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Hu D, Duan Y, Chen Y, Li B, Du Y, Shi S. A case report of gastrointestinal stromal tumor of the duodenum. Am J Transl Res 2022; 14:8279-8285. [PMID: 36505329 PMCID: PMC9730101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Accepted: 10/28/2022] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Gastrointestinal stromal tumors (GISTs) rarely occur in the duodenum, and only a few cases have been reported. Its clinical manifestations are not specific, and the imaging examination results are not typical, so a preoperative diagnosis is difficult. Pathologic examinations and genetic testing after surgical resection are the main diagnostic methods. Here, a case of duodenal stromal tumor complicated by gastrointestinal perforation is reported. A 57-year-old man presented with paroxysmal abdominal pain and bloating for 7 days. Contrast-enhanced computed tomography of the abdomen revealed a large mass (10 cm in diameter) in the right upper abdomen, which was considered neoplastic. The mass was anterior and inferior to the head of the pancreas, and medial to the mesenteric vessels. The tumor surrounded the descending and horizontal parts of the duodenum, and it ruptured into the lumen of the descending duodenum. After the patient underwent tumor resection, we found a rupture of the descending duodenal opening. After that, duodenal fistula drainage, gastrostomy, jejunostomy, small intestinal adhesion release and abdominal irrigation drainage were performed. Immunohistochemical staining results were as follows: CD34 (-), desmin (-), S-100 (-), CD117 (9.7) (+), DoG-1 (+), SDHB (+), Ki-67 (+5%). Based on these results, the lesion was finally diagnosed as duodenal GIST. The patient underwent surgical resection without targeted therapy and recovered well. DISCUSSION Duodenal stromal tumors often present with gastrointestinal bleeding and other clinical symptoms, requiring urgent surgery. Complete resection of the tumor is an effective surgical method. Extended resection does not prolong survival. However, surgical treatment should be determined according to the size and location of the tumor and its relationship to the pancreas. This highly malignant duodenal stromal tumor was >10 cm, accompanied by gastrointestinal perforation and necrosis. Surgical resection was required while protecting the organ function.
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Affiliation(s)
- Danqiong Hu
- Department of Gastroenterology, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
| | - Yangri Duan
- Department of Gastroenterology, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
| | - Yonghua Chen
- Department of Emergency, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
| | - Bingfeng Li
- Department of General Surgery, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
| | - Yechun Du
- Department of Gastroenterology, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
| | - Shuimei Shi
- Department of Internal Medicine-Cardiovascular, The Third People’s Hospital of Yuhang DistrictHangzhou 311100, Zhejiang, China
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12
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Li W, Gordon AC, Mouli SK. Editorial for "Assessment of Prognostic Factors and Molecular Subtypes of Breast Cancer With a Continuous-Time Random-Walk MR Diffusion Model: Using Whole Tumor Histogram Analysis". J Magn Reson Imaging 2022. [PMID: 36205703 DOI: 10.1002/jmri.28476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 11/08/2022] Open
Affiliation(s)
- Weiguo Li
- Department of Radiology, Northwestern University, Chicago, Illinois, USA.,Department of Biomedical engineering, University of Illinois at Chicago, Chicago, Illinois, USA.,Research Resource Center, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Andrew C Gordon
- Department of Radiology, Northwestern University, Chicago, Illinois, USA
| | - Samdeep K Mouli
- Department of Radiology, Northwestern University, Chicago, Illinois, USA
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Luo Y, Jiang H, Meng N, Huang Z, Li Z, Feng P, Fang T, Fu F, Yuan J, Wang Z, Yang Y, Wang M. A comparison study of monoexponential and fractional order calculus diffusion models and 18F-FDG PET in differentiating benign and malignant solitary pulmonary lesions and their pathological types. Front Oncol 2022; 12:907860. [PMID: 35936757 PMCID: PMC9351313 DOI: 10.3389/fonc.2022.907860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/28/2022] [Indexed: 11/24/2022] Open
Abstract
Objective To evaluate the application value of monoexponential, fractional order calculus (FROC) diffusion models and PET imaging to distinguish between benign and malignant solitary pulmonary lesions (SPLs) and malignant SPLs with different pathological types and explore the correlation between each parameter and Ki67 expression. Methods A total of 112 patients were enrolled in this study. Prior to treatment, all patients underwent a dedicated thoracic 18F-FDG PET/MR examination. Five parameters [including apparent diffusion coefficient (ADC) derived from the monoexponential model; diffusion coefficient (D), a microstructural quantity (μ), and fractional order parameter (β) derived from the FROC model and maximum standardized uptake value (SUVmax) derived from PET] were compared between benign and malignant SPLs and different pathological types of malignant SPLs. Independent sample t test, Mann-Whitney U test, DeLong test and receiver operating characteristic (ROC) curve analysis were used for statistical evaluation. Pearson correlation analysis was used to calculate the correlations between Ki-67 and ADC, D, μ, β, and SUVmax. Results The ADC and D values were significantly higher and the μ and SUVmax values were significantly lower in the benign group [1.57 (1.37, 2.05) μm2/ms, 1.59 (1.52, 1.72) μm2/ms, 5.06 (3.76, 5.66) μm, 5.15 ± 2.60] than in the malignant group [1.32 (1.03, 1.51) μm2/ms, 1.43 (1.29, 1.52) μm2/ms, 7.06 (5.87, 9.45) μm, 9.85 ± 4.95]. The ADC, D and β values were significantly lower and the μ and SUVmax values were significantly higher in the squamous cell carcinoma (SCC) group [1.29 (0.66, 1.42) μm2/ms, 1.32 (1.02, 1.42) μm2/ms, 0.63 ± 0.10, 9.40 (7.76, 15.38) μm, 11.70 ± 5.98] than in the adenocarcinoma (AC) group [1.40 (1.28, 1.67) μm2/ms, 1.52 (1.44, 1.64) μm2/ms, 0.70 ± 0.10, 5.99 (4.54, 6.87) μm, 8.76 ± 4.18]. ROC curve analysis showed that for a single parameter, μ exhibited the best AUC value in discriminating between benign and malignant SPLs groups and AC and SCC groups (AUC = 0.824 and 0.911, respectively). Importantly, the combination of monoexponential, FROC models and PET imaging can further improve diagnostic performance (AUC = 0.872 and 0.922, respectively). The Pearson correlation analysis showed that Ki67 was positively correlated with μ value and negatively correlated with ADC and D values (r = 0.402, -0.346, -0.450, respectively). Conclusion The parameters D and μ derived from the FROC model were superior to ADC and SUVmax in distinguishing benign from malignant SPLs and adenocarcinoma from squamous cell carcinoma, in addition, the combination of multiple parameters can further improve diagnostic performance. The non-Gaussian FROC diffusion model is expected to become a noninvasive quantitative imaging technique for identifying SPLs.
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Affiliation(s)
- Yu Luo
- Department of Medical Imaging, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Han Jiang
- Department of Medical Imaging, Xinxiang Medical University & Henan Provincial People’s Hospital, Xinxiang, Henan, China
| | - Nan Meng
- Department of Medical Imaging, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Zhun Huang
- Department of Medical Imaging, Henan University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
| | - Ziqiang Li
- Department of Medical Imaging, Xinxiang Medical University & Henan Provincial People’s Hospital, Xinxiang, Henan, China
| | - Pengyang Feng
- Department of Medical Imaging, Henan University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
| | - Ting Fang
- Department of Medical Imaging, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Fangfang Fu
- Department of Medical Imaging, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People’s Hospital & Henan Provincial People’s Hospital, Zhengzhou, China
- Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
- *Correspondence: Meiyun Wang,
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Sheng R, Zhang Y, Sun W, Ji Y, Zeng M, Yao X, Dai Y. Staging Chronic Hepatitis B Related Liver Fibrosis with a Fractional Order Calculus Diffusion Model. Acad Radiol 2022; 29:951-963. [PMID: 34429260 DOI: 10.1016/j.acra.2021.07.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 07/06/2021] [Accepted: 07/07/2021] [Indexed: 12/17/2022]
Abstract
RATIONALE AND OBJECTIVES Accurately staging liver fibrosis is of great clinical significance. We aimed to evaluate the clinical potential of the non-Gaussian fractional order calculus (FROC) diffusion model in staging liver fibrosis. MATERIALS AND METHODS A total of 82 patients with chronic hepatitis B (CHB) were included in this prospective study. Diffusion weighted imaging (DWI)-derived parameters including the diffusion coefficient (D), fractional order parameter (β) and microstructural quantity (μ) sourced from FROC-DWI, and apparent diffusion coefficient (ADC) derived from mono-exponential DWI, as well as the aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 (FIB-4) were calculated. Their correlations with fibrosis stages and the diagnostic efficacy in predicting liver fibrosis were assessed and compared. RESULTS D (r = -0.667), β (r = -0.671), μ (r = -0.481), and ADC (r = -0.665) displayed significant correlations with fibrosis stages (p < 0.001). D, β and ADC (p < 0.01) were independently associated with fibrosis; and compared to inflammatory activity, fibrosis was the independent factor significantly correlated with D, β and ADC (p < 0.001). There were no significant differences between the area under curves of D, β, μ or their combinations and ADC for predicting different fibrosis stages (p > 0.05). The diagnostic performance of the combined index with four diffusion metrics was better than D, β, μ or ADC used alone (p < 0.05) as well as APRI or FIB-4 (p < 0.01) in fibrosis staging. CONCLUSION FROC-DWI was valuable in staging liver fibrosis in patients with CHB, but there were no significant differences between the FROC-DWI parameters and the classical ADC. However, the combined DWI-derived index including D, β, μ and ADC offered the best diagnostic efficacy and may serve as a reliable tool for fibrosis evaluation, superior to APRI and FIB-4.
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Affiliation(s)
- Ruofan Sheng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yunfei Zhang
- Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Wei Sun
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yuan Ji
- Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Mengsu Zeng
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China.
| | - Xiuzhong Yao
- Department of Radiology, Zhongshan Hospital, Fudan University; Shanghai Institute of Medical Imaging, No. 180 Fenglin Road, Xuhui District, Shanghai, China
| | - Yongming Dai
- Central Research Institute, United Imaging Healthcare, Shanghai, China
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Li W. Non-Gaussian Diffusion MRI for Evaluating Hepatic Fibrosis. Acad Radiol 2022; 29:964-966. [PMID: 35597754 DOI: 10.1016/j.acra.2022.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 04/16/2022] [Accepted: 04/21/2022] [Indexed: 11/01/2022]
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16
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Guo Y, Chen J, Zhang Y, Guo Y, Jiang M, Dai Y, Yao X. Differentiating Cytokeratin 19 expression of hepatocellular carcinoma by using multi-b-value diffusion-weighted MR imaging with mono-exponential, stretched exponential, intravoxel incoherent motion, diffusion kurtosis imaging and fractional order calculus models. Eur J Radiol 2022; 150:110237. [DOI: 10.1016/j.ejrad.2022.110237] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 02/02/2022] [Accepted: 03/03/2022] [Indexed: 12/25/2022]
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Shao X, An L, Liu H, Feng H, Zheng L, Dai Y, Yu B, Zhang J. Cervical Carcinoma: Evaluation Using Diffusion MRI With a Fractional Order Calculus Model and its Correlation With Histopathologic Findings. Front Oncol 2022; 12:851677. [PMID: 35480091 PMCID: PMC9036957 DOI: 10.3389/fonc.2022.851677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 03/03/2022] [Indexed: 11/13/2022] Open
Abstract
Objective The objective of the study is to investigate the feasibility of using the fractional order calculus (FROC) model to reflect tumor subtypes and histological grades of cervical carcinoma. Methods Sixty patients with untreated cervical carcinoma underwent multi-b-value diffusion-weighted imaging (DWI) at 3.0T magnetic resonance imaging (MRI). The mono-exponential and the FROC models were fitted. The differences in the histological subtypes and grades were evaluated by the Mann–Whitney U test. Receiver operating characteristic (ROC) analyses were performed to assess the diagnostic performance and to determine the best predictor for both univariate analysis and multivariate analysis. Differences between ROC curves were tested using the Hanley and McNeil test, while the sensitivity, specificity, and accuracy were compared using the McNemar test. P-value <0.05 was considered as significant difference. The Bonferroni corrections were applied to reduce problems associated with multiple comparisons. Results Only the parameter β, derived from the FROC model could differentiate cervical carcinoma subtypes (P = 0.03) and the squamous cell carcinoma (SCC) lesions exhibited significantly lower β than that in the adenocarcinoma (ACA) lesions. All the individual parameters, namely, ADC, β, D, and μ derived from the FROC model, could differentiate low-grade cervical carcinomas from high-grade ones (P = 0.022, 0.009, 0.004, and 0.015, respectively). The combination of all the FROC parameters showed the best overall performance, providing the highest sensitivity (81.2%) and AUC (0.829). Conclusion The parameters derived from the FROC model were able to differentiate the subtypes and grades of cervical carcinoma.
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Affiliation(s)
- Xian Shao
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
| | - Li An
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
| | - Hui Liu
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Hui Feng
- Department of Radiology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Liyun Zheng
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Yongming Dai
- MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Bin Yu
- Department of Emergency, The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Jin Zhang
- Department of Anesthesiology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China
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Shi B, Xue K, Yin Y, Xu Q, Shi B, Wu D, Ye J. Grading of clear cell renal cell carcinoma using diffusion MRI with a fractional order calculus model. Acta Radiol 2022; 64:421-430. [PMID: 35040361 DOI: 10.1177/02841851211072482] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND The fractional order calculus (FROC) model has been developed to describe restrained motion of water molecules as well as microstructural heterogeneity, providing a novel tool for non-invasive tumor grading. PURPOSE To evaluate the role of the FROC model in characterizing clear cell renal cell carcinoma (ccRCC) grades. MATERIAL AND METHODS A total of 59 patients diagnosed with ccRCC were included in this prospective study. The diffusion metrics derived from the mono-exponential model (apparent diffusion coefficient [ADC]), intra-voxel incoherent motion [IVIM] model [D, D*, f], and FROC model [Dfroc, β, μ]) were calculated and compared between low- and high-grade ccRCCs. Binary logistic regression analysis was performed to establish the diagnostic models. Receiver operating characteristic (ROC) analysis and DeLong test were performed to evaluate and compare the diagnostic performance of metrics in grading ccRCC. RESULTS All the metrics except D* and f exhibited statistical differences between low- and high-grade ccRCCs. ROC analysis showed individual FROC parameters, μ, Dfroc, and β, outperformed ADC and IVIM parameters in grading ccRCC. For single parameter, μ demonstrated the highest AUC value, sensitivity, and diagnostic accuracy in discriminating the two ccRCC groups while β exhibited the optimal specificity. Importantly, the combination of Dfroc, μ, and β could further improve the diagnostic performance. CONCLUSION The FROC parameters were superior to ADC and IVIM parameters in grading ccRCC, indicating the great potential of the FROC model in distinguishing low- and high-grade ccRCCs.
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Affiliation(s)
- Bowen Shi
- Department of Medical Imaging, Clinic Medical School, Yangzhou University, Northern Jiangsu Province Hospital, Yangzhou, PR China
| | - Ke Xue
- Central Research Institute, United Imaging Healthcare, Shanghai, PR China
| | - Yili Yin
- Department of Medical Imaging, Clinic Medical School, Yangzhou University, Northern Jiangsu Province Hospital, Yangzhou, PR China
| | - Qing Xu
- Department of Medical Imaging, Clinic Medical School, Yangzhou University, Northern Jiangsu Province Hospital, Yangzhou, PR China
| | - Binbin Shi
- Department of Medical Imaging, Clinic Medical School, Yangzhou University, Northern Jiangsu Province Hospital, Yangzhou, PR China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, Shanghai, PR China
| | - Jing Ye
- Department of Medical Imaging, Clinic Medical School, Yangzhou University, Northern Jiangsu Province Hospital, Yangzhou, PR China
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Predicting the aggressiveness of peripheral zone prostate cancer using a fractional order calculus diffusion model. Eur J Radiol 2021; 143:109913. [PMID: 34464907 DOI: 10.1016/j.ejrad.2021.109913] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/01/2021] [Accepted: 08/12/2021] [Indexed: 11/21/2022]
Abstract
PURPOSE To evaluate the performance of parameters D, β, μ from the Fractional Order Calculus (FROC) model at differentiating peripheral zone (PZ) prostate cancer (PCa) MATERIAL AND METHODS: 75 patients who underwent targeted MRI-guided TRUS prostate biopsy within 6 months of MRI were reviewed retrospectively. Regions of interest (ROI) were placed on suspicious lesions on MRI scans. ROIs were then correlated to pathological results based on core biopsy location. The final tumor count is a total: 23 of GS 6 (3 + 3), 36 of GS 7 (3 + 4), 18 of GS 7 (4 + 3), and 19 of GS ≥ 8. Diffusion-weighted imaging (DWI) scans were fitted into the FROC and monoexponential model to calculate ADC and FROC parameters: anomalous diffusion coefficient D, intravoxel diffusion heterogeneity β, and spatial parameter μ. The performance of FROC parameters and ADC at differentiating PCa grade was evaluated with receiver operating characteristic (ROC) analysis. RESULTS In differentiating low (GS 6) vs. intermediate (GS 7) risk PZ PCa, combination of (D, β) provides the best performance with AUC of 0.829 with significance of p = 0.018 when compared to ADC (AUC of 0.655). In differentiating clinically significant (GS 6) vs. clinically significant (GS ≥ 7) PCa, combination of (D, β, μ) provides highest AUC of 0.802 when compared to ADC (AUC of 0.671) with significance of p = 0.038. Stratification of intermediate (GS 7) and high (GS ≥ 8) risk PCa with FROC did not reach a significant difference when compared to ADC. CONCLUSION Combination of FROC parameters shows greater performance than ADC at differentiating low vs. intermediate risk and clinically insignificant vs. significant prostate cancers in peripheral zone lesions. The FROC diffusion model holds promise as a quantitative imaging technique for non-invasive evaluation of PZ PCa.
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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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21
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Liu G, Lu Y, Dai Y, Xue K, Yi Y, Xu J, Wu D, Wu G. Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone. Abdom Radiol (NY) 2021; 46:2740-2750. [PMID: 33388809 DOI: 10.1007/s00261-020-02903-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 12/01/2020] [Accepted: 12/06/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ. METHODS 80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (Ds), fast diffusion coefficient (Df),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (β), and spatial metric (μ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. RESULTS The areas under the ROC curve (AUC) values of β derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of β was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089). CONCLUSION Although no significant difference was found in distinguishing PCa from BPH, the metric β derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ.
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Affiliation(s)
- Guiqin Liu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | - Yang Lu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | | | - Ke Xue
- United Imaging Healthcare, Shanghai, China
| | | | - Jianrong Xu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, 3663 N. Zhongshan Road, Shanghai, 200062, China.
| | - Guangyu Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
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22
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Mokry T, Pantke J, Mlynarska-Bujny A, Hasse FC, Kuder TA, Schlemmer HP, Kauczor HU, Rom J, Bickelhaupt S. Diffusivity mapping of the ovaries: Variability of apparent diffusion and kurtosis variables over the menstrual cycle and influence of oral contraceptives. Magn Reson Imaging 2021; 80:50-57. [PMID: 33905830 DOI: 10.1016/j.mri.2021.04.006] [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: 11/18/2020] [Revised: 04/14/2021] [Accepted: 04/21/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE We aimed to investigate whether quantitative diffusivity variables of healthy ovaries vary during the menstrual cycle and to evaluate alterations in women using oral contraceptives (OC). METHODS This prospective study (S-339/2016) included 30 healthy female volunteers, with (n = 15) and without (n = 15) intake of OC between 07/2017 and 09/2019. Participants underwent 3T diffusion-weighted MRI (b-values 0-2000 s/mm2) three times during a menstrual cycle (T1 = day 1-5; T2 = day 7-12; T3 = day 19-24). Both ovaries were manually three-dimensionally segmented on b = 1500 s/mm2; apparent diffusion coefficient (ADC) calculation and kurtosis fitting (Dapp, Kapp) were performed. Differences in ADC, Dapp and Kapp between time points and groups were compared using repeated measures ANOVA and t-test after Shapiro-Wilk and Brown-Forsythe test for normality and equal variance. RESULTS In women with a natural menstrual cycle, ADC and kurtosis variables showed significant changes in ovaries with the dominant follicle between T1 vs T2 and T1 vs T3, whilst no differences were observed between T2 vs T3: ADC ± SD for T1 1.524 ± 0.160, T2 1.737 ± 0.160, and T3 1.747 ± 0.241 μm2/ms (p = 0.01 T2 vs T1; p = 1.0 T2 vs T3, p = 0.003 T3 vs T1); Dapp ± SD for T1 2.018 ± 0.140, T2 2.272 ± 0.189, and T3 2.230 ± 0.256 μm2/ms (p = 0.003 T2 vs T1, p = 1.0 T2 vs T3, p = 0.02 T3 vs T1); Kapp ± SD for T1 0.614 ± 0.0339, T2 0.546 ± 0.0637, and T3 0.529 ± 0.0567 (p < 0.001 T2 vs T1, p = 0.86 T2 vs T3, p < 0.001 T3 vs T1). No significant differences were found in the contralateral ovaries or in females taking OC. CONCLUSION Physiological cycle-dependent changes in quantitative diffusivity variables of ovaries should be considered especially when interpreting radiomics analyses in reproductive women.
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Affiliation(s)
- Theresa Mokry
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany.
| | - Judith Pantke
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
| | - Anna Mlynarska-Bujny
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany; Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Germany
| | - Felix Christian Hasse
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
| | - Tristan Anselm Kuder
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | | | - Hans-Ulrich Kauczor
- Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Im Neuenheimer Feld 110, 69120 Heidelberg, Germany
| | - Joachim Rom
- Hospital for General Obstetrics and Gynecology, Hospital Frankfurt Hoechst, Frankfurt, Germany
| | - Sebastian Bickelhaupt
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany; Junior Group Medical Imaging and Radiology - Cancer Prevention, German Cancer Research Center, Heidelberg, Germany; Institute of Radiology, Erlangen University Hospital, Erlangen, Germany
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Karaman MM, Zhang J, Xie KL, Zhu W, Zhou XJ. Quartile histogram assessment of glioma malignancy using high b-value diffusion MRI with a continuous-time random-walk model. NMR IN BIOMEDICINE 2021; 34:e4485. [PMID: 33543512 DOI: 10.1002/nbm.4485] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 01/15/2021] [Indexed: 06/12/2023]
Abstract
The purpose of this study is to investigate the feasibility of using a continuous-time random-walk (CTRW) diffusion model, together with a quartile histogram analysis, for assessing glioma malignancy by probing tissue heterogeneity as well as cellularity. In this prospective study, 91 patients (40 females, 51 males) with histopathologically proven gliomas underwent MRI at 3 T. The cohort included 42 grade II (GrII), 19 grade III (GrIII) and 29 grade IV (GrIV) gliomas. Echo-planar diffusion-weighted imaging was conducted using 17 b-values (0-4000 s/mm2 ). Three CTRW model parameters, including an anomalous diffusion coefficient Dm , and two parameters related to temporal and spatial diffusion heterogeneity α and β, respectively, were obtained. The mean parameter values within the tumor regions of interest (ROIs) were computed by utilizing the first quartile of the histograms as well as the full ROI for comparison. A Bonferroni-Holm-corrected Mann-Whitney U-test was used for the group comparisons. Individual and combinations of the CTRW parameters were evaluated for the characterization of gliomas with a receiver operating characteristic analysis. All first-quartile mean CTRW parameters yielded significant differences (p-values < 0.05) between pair-wise comparisons of GrII (Dm : 1.14 ± 0.37 μm2 /ms; α: 0.904 ± 0.03, β: 0.913 ± 0.06), GrIII (Dm : 0.88 ± 0.21 μm2 /ms; α: 0.888 ± 0.01, β: 0.857 ± 0.06) and GrIV gliomas (Dm : 0.73 ± 0.22 μm2 /ms; α: 0.878 ± 0.01; β: 0.791 ± 0.07). The highest sensitivity, specificity, accuracy and area-under-the-curve of using the combinations of the first-quartile parameters were 84.2%, 78.5%, 75.4% and 0.76 for GrII and GrIII classification; 86.2%, 89.4%, 75% and 0.76 for GrIII and GrIV classification; and 86.2%, 85.7%, 84.5% and 0.90 for GrII and GrIV classification, respectively. Quartile-based analysis produced higher accuracy and area-under-the-curve than the full ROI-based analysis in all classifications. The CTRW diffusion model, together with a quartile-based histogram analysis, offers a new way for probing tumor structural heterogeneity at a subvoxel level, and has potential for in vivo assessment of glioma malignancy to complement histopathology.
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Affiliation(s)
- M Muge Karaman
- Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Jiaxuan Zhang
- Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Karen L Xie
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaohong Joe Zhou
- Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, Illinois, USA
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24
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Karaman MM, Tang L, Li Z, Sun Y, Li JZ, Zhou XJ. In vivo assessment of Lauren classification for gastric adenocarcinoma using diffusion MRI with a fractional order calculus model. Eur Radiol 2021; 31:5659-5668. [PMID: 33616764 DOI: 10.1007/s00330-021-07694-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 12/21/2020] [Accepted: 01/18/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To evaluate the performance of a fractional order calculus (FROC) diffusion model for imaging-based assessment of Lauren classification in gastric adenocarcinoma. METHODS In this study, 43 patients (15 females, 28 males) with gastric adenocarcinoma underwent MRI at 1.5 T. According to pathology-based Lauren classification, 10 patients had diffuse-type, 20 had intestinal-type, and 13 had mixed-type lesions. The diffuse and mixed types were combined as diffuse-and-mixed type to be differentiated from the intestinal type using diffusion MRI. Diffusion-weighted images were acquired by using eleven b-values (0-2000 s/mm2). Three FROC model parameters comprising diffusion coefficient D, intravoxel diffusion heterogeneity β, and a microstructural quantity μ, together with a conventional apparent diffusion coefficient (ADC), were estimated. The mean parameter values in the tumour were computed by using a percentile histogram analysis. Individual or linear combinations of the mean parameters in the tumour were used to differentiate the diffuse-and-mixed type from the intestinal type using descriptive statistics and receiver operating characteristic (ROC) analyses. RESULTS Significant differences were observed between diffuse-and-mixed-type and intestinal-type lesions in D (0.99 ± 0.20 μm2/ms vs. 1.11 ± 0.23 μm2/ms; p = 0.036), β (0.37 ± 0.08 vs. 0.43 ± 0.11; p = 0.043), μ (7.92 ± 2.79 μm vs. 9.87 ± 1.52 μm; p = 0.038), and ADC (0.81 ± 0.34 μm2/ms vs. 0.96 ± 0.19 μm2/ms; p = 0.033). Among the individual parameters, μ produced the largest area under the ROC curve (0.739). The combinations of (D, β, μ) and (β and μ) produced the best overall performance with a sensitivity of 0.739, specificity of 0.750, accuracy of 0.744, and area under the curve of 0.793 (95% confidence interval: 0.657-0.929). CONCLUSION Diffusion MRI with the FROC model holds promise for non-invasive assessment of Lauren classification for gastric adenocarcinoma. KEY POINTS • High b-value diffusion MRI with a FROC model that is sensitive to tissue microstructures can differentiate the diffuse-and-mixed type from intestinal type of gastric adenocarcinoma. • The combination of FROC parameters produced the best result for distinguishing the diffuse-and-mixed type from the intestinal type with an area under the receiver operating characteristic curve of 0.793. • The FROC model parameters, individually or conjointly, hold promise for repeated, non-invasive evaluations of gastric adenocarcinoma at various time points throughout disease progression or regression to complement conventional Lauren classification.
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Affiliation(s)
- M Muge Karaman
- Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA.,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Lei Tang
- Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Ziyu Li
- Department of Gastrointestinal Surgery, Peking University Cancer Hospital and Institute, Beijing, China
| | - Yu Sun
- Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Jia-Zheng Li
- Department of Radiology, Peking University Cancer Hospital and Institute, Beijing, China
| | - Xiaohong Joe Zhou
- Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA. .,Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA. .,Departments of Radiology and Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA. .,Center for Magnetic Resonance Research, University of Illinois at Chicago, 2242 West Harrison Street, Suite 103, M/C 831, Chicago, IL, 60612, USA.
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Tavakoli AA, Kuder TA, Tichy D, Radtke JP, Görtz M, Schütz V, Stenzinger A, Hohenfellner M, Schlemmer HP, Bonekamp D. Measured Multipoint Ultra-High b-Value Diffusion MRI in the Assessment of MRI-Detected Prostate Lesions. Invest Radiol 2021; 56:94-102. [PMID: 32930560 DOI: 10.1097/rli.0000000000000712] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVES The aim of this study was to assess quantitative ultra-high b-value (UHB) diffusion magnetic resonance imaging (MRI)-derived parameters in comparison to standard clinical apparent diffusion coefficient (SD-ADC-2b-1000, SD-ADC-2b-1500) for the prediction of clinically significant prostate cancer, defined as Gleason Grade Group greater than or equal to 2. MATERIALS AND METHODS Seventy-three patients who underwent 3-T prostate MRI with diffusion-weighted imaging acquired at b = 50/500/1000/1500s/mm2 and b = 100/500/1000/1500/2250/3000/4000 s/mm2 were included. Magnetic resonance lesions were segmented manually on individual sequences, then matched to targeted transrectal ultrasonography/MRI fusion biopsies. Monoexponential 2-point and multipoint fits of standard diffusion and of UHB diffusion were calculated with incremental b-values. Furthermore, a kurtosis fit with parameters Dapp and Kapp with incremental b-values was obtained. Each parameter was examined for prediction of clinically significant prostate cancer using bootstrapped receiver operating characteristics and decision curve analysis. Parameter models were compared using Vuong test. RESULTS Fifty of 73 men (age, 66 years [interquartile range, 61-72]; prostate-specific antigen, 6.6 ng/mL [interquartile range, 5-9.7]) had 64 MRI-detected lesions. The performance of SD-ADC-2b-1000 (area under the curve, 0.82) and SD-ADC-2b-1500 (area under the curve, 0.82) was not statistically different (P = 0.99), with SD-ADC-2b-1500 selected as reference. Compared with the reference model, none of the 19 tested logistic regression parameter models including multipoint and 2-point UHB-ADC, Dapp, and Kapp with incremental b-values of up to 4000 s/mm2 outperformed SD-ADC-2b-1500 (all P's > 0.05). Decision curve analysis confirmed these results indicating no higher net benefit for UHB parameters in comparison to SD-ADC-2b-1500 in the clinically important range from 3% to 20% of cancer threshold probability. Net reduction analysis showed no reduction of MR lesions requiring biopsy. CONCLUSIONS Despite evaluation of a large b-value range and inclusion of 2-point, multipoint, and kurtosis models, none of the parameters provided better predictive performance than standard 2-point ADC measurements using b-values 50/1000 or 50/1500. Our results suggest that most of the diagnostic benefits available in diffusion MRI are already represented in an ADC composed of one low and one 1000 to 1500 s/mm2 b-value.
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Affiliation(s)
| | | | - Diana Tichy
- Division of Biostatistics, German Cancer Research Center (DKFZ)
| | | | - Magdalena Görtz
- Department of Urology, University of Heidelberg Medical Center
| | - Viktoria Schütz
- Department of Urology, University of Heidelberg Medical Center
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Chen W, Zhu LN, Dai YM, Jiang JS, Bu SS, Xu XQ, Wu FY. Differentiation of salivary gland tumor using diffusion-weighted imaging with a fractional order calculus model. Br J Radiol 2020; 93:20200052. [PMID: 32649236 DOI: 10.1259/bjr.20200052] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
OBJECTIVE To evaluate the feasibility of using imaging parameters (D, β and μ) obtained from fractional order calculus (FROC) diffusion model to differentiate salivary gland tumors. METHODS 15 b-value (0-2000 s/mm2) diffusion-weighted imaging (DWI) was scanned in 62 patients with salivary gland tumors (47 benign and 15 malignant). Diffusion coefficient D, fractional order parameter β (which correlates with tissue heterogeneity) and a microstructural quantity μ of the solid portion within the tumor were calculated, and compared between benign and malignant groups, or among pleomorphic adenoma (PA), Warthin's tumor (WT), and malignant tumor (MT) groups. Performance of FROC parameters for differentiation was assessed using receiver operating characteristic analysis. RESULTS None of the FROC parameters exhibited significant differences between benign and malignant group (D, p = 0.150; β, p = 0.967; μ, p = 0.693). WT showed significantly lower D (p < 0.001) and β (p < 0.001), while higher μ (p = 0.001) than PA. Combination of D, β and μ showed optimal diagnostic performance (area under the curve, AUC, 0.998). MT showed significantly lower D (p = 0.001) and β (p = 0.025) than PA, while no significant difference was found on μ (p = 0.064). Combination of D and β showed optimal diagnostic performance (AUC, 0.933). Significant difference was found on β (p = 0.027) between MT and WT, while not on D (p = 0.806) and μ (p = 0.789). Setting a βof 0.615 as the cut-off value, optimal diagnostic performance could be obtained (AUC = 0.806). CONCLUSION A non-Gaussian FROC diffusion model can serve as a noninvasive and quantitative imaging technique for differentiating salivary gland tumors. ADVANCES IN KNOWLEDGE (1) PA showed higher D and β and lower μ than WT. (2) PA had higher D and β than MT. (3) WT demonstrated lower β than MT. (4) β, as a new FROC parameter, could offer an added value to the differentiation.
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Affiliation(s)
- Wei Chen
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Liu-Ning Zhu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yong-Ming Dai
- United Imaging Healthcare, Central Research Institute, Shanghai, China
| | - Jia-Suo Jiang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shou-Shan Bu
- Department of Stomatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiao-Quan Xu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Fei-Yun Wu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Fu J, Tang L, Li ZY, Li XT, Zhu HF, Sun YS, Ji JF. Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy. Eur J Radiol 2020; 128:108974. [PMID: 32416553 DOI: 10.1016/j.ejrad.2020.108974] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 02/15/2020] [Accepted: 03/19/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE To assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC). METHODS A total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 01, 2001, 5001, 8002, 10004, 15004, 20006 s/mm2, the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm2) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0-2, poor response group: TRG 3). Mann-Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis. RESULTS There were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MKpre and MKpost values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADCpost and MDpost in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MKpost (AUC = 0.958, cutoff value = 0.614). The MKpre and MKpost had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively. CONCLUSION Both DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MKpost displayed the best performance.
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Affiliation(s)
- Jia Fu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology Department, Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China; Department of Radiology, Civil Aviation General Hospital, No. 1 Gaojingjia, Chaoyang Road, Chaoyang District, Beijing 100123, China.
| | - Lei Tang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology Department, Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China.
| | - Zi-Yu Li
- Department of Gastrointestinal Cancer Center Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China.
| | - Xiao-Ting Li
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology Department, Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China.
| | - Hai-Feng Zhu
- Department of Radiology, Civil Aviation General Hospital, No. 1 Gaojingjia, Chaoyang Road, Chaoyang District, Beijing 100123, China.
| | - Ying-Shi Sun
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Radiology Department, Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China.
| | - Jia-Fu Ji
- Department of Gastrointestinal Cancer Center Surgery, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Peking University Cancer Hospital & Institute, No. 52 Fu-Cheng Road, Hai-Dian District, Beijing 100142, China.
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Lu J, Zhou Z, Morelli JN, Yu H, Luo Y, Hu X, Li Z, Hu D, Shen Y. A Systematic Review of Technical Parameters for MR of the Small Bowel in non-IBD Conditions over the Last Ten Years. Sci Rep 2019; 9:14100. [PMID: 31575890 PMCID: PMC6773732 DOI: 10.1038/s41598-019-50501-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 09/13/2019] [Indexed: 12/27/2022] Open
Abstract
Technical guidelines for magnetic resonance imaging (MRI) of the small bowel (SB) in the setting of inflammatory bowel diseases (IBDs) were detailed in a 2017 consensus issued by European Society of Gastrointestinal and Abdominal Radiology (ESGAR) and European Society of Pediatric Radiology (ESPR); however, MRI for non-IBD conditions was not addressed. Hence, we performed a systematic review collecting researches on SB MRI for non-IBDs. The literatures were then divided into morphologic group and functional group. Information about the MRI techniques, gastrointestinal preparation, and details of cine-MRI protocols was extracted. We found that a 1.5 T MRI system, prone positioning, and MR enterography were frequently utilized in clinical practice. Gadolinium contrast sequences were routinely implemented, while diffusion-weighted imaging (DWI) was much less performed. The gastrointestinal preparation varied throughout the studies. No uniform protocols for cine imaging could be established. SB MRI examinations for non-IBDs are far from standardized, especially for functional studies. Recommendations for standard parameters in cine-MRI sequences are difficult to make due to lack of evidentiary support. MRI investigations in non-IBD conditions are needed and the standardization of non-IBD imaging in clinical practice is required.
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Affiliation(s)
- Jingyu Lu
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.,Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Ziling Zhou
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | | | - Hao Yu
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yan Luo
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xuemei Hu
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhen Li
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Daoyu Hu
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yaqi Shen
- Departments of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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Zhong Z, Merkitch D, Karaman MM, Zhang J, Sui Y, Goldman JG, Zhou XJ. High-Spatial-Resolution Diffusion MRI in Parkinson Disease: Lateral Asymmetry of the Substantia Nigra. Radiology 2019; 291:149-157. [PMID: 30777809 DOI: 10.1148/radiol.2019181042] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Motor symptoms in Parkinson disease (PD) have exhibited lateral asymmetry, suggesting asymmetric neuronal loss in the substantia nigra (SN). Diffusion MRI may be able to help confirm tissue microstructural alterations in the substantia nigra to probe for the presence of asymmetry. Purpose To investigate lateral asymmetry in the SN of patients with PD by using diffusion MRI with both Gaussian and non-Gaussian models. Materials and Methods In this cross-sectional study conducted from March 2015 to March 2017, 27 participants with PD and 27 age-matched healthy control (HC) participants, all right handed, underwent MRI at 3.0 T. High-spatial-resolution diffusion images were acquired with a reduced field of view by using seven b values up to 3000 sec/mm2. A continuous-time random-walk (CTRW) non-Gaussian diffusion model was used to produce anomalous diffusion coefficient (Dm) and temporal (α) and spatial (β) diffusion heterogeneity indexes followed by a Gaussian diffusion model to yield an apparent diffusion coefficient (ADC). Individual or linear combinations of diffusion parameters in the SN were unilaterally and bilaterally compared between the PD and HC groups. Results In the bilateral comparison between the PD and HC groups, differences were observed in β (0.67 ± 0.06 [standard deviation] vs 0.64 ± 0.04, respectively; P = .016), ADC (0.48 μm2/msec ± 0.08 vs 0.53 μm2/msec ± 0.06, respectively; P = .03), and the combination of CTRW parameters (P = .02). In the unilateral comparison, differences were observed in all diffusion parameters on the left SN (P < .03), but not on the right (P > .20). In a receiver operating characteristic (ROC) analysis to delineate left SN abnormality in PD, the combination of Dm, α, and β produced the best sensitivity (sensitivity, 0.78); the combination of Dm and β produced the best specificity (specificity, 0.85); and the combination of α and β produced the largest area under the ROC curve (area under the ROC curve, 0.73). Conclusion These results suggest that quantitative diffusion MRI is sensitive to brain tissue changes in participants with Parkinson disease and provide evidence of substantia nigra lateral asymmetry in this disease. © RSNA, 2019 Online supplemental material is available for this article.
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Affiliation(s)
- Zheng Zhong
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Douglas Merkitch
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - M Muge Karaman
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Jiaxuan Zhang
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Yi Sui
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Jennifer G Goldman
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
| | - Xiaohong Joe Zhou
- From the Center for Magnetic Resonance Research (Z.Z., M.M.K., J.Z., Y.S., X.J.Z.), Departments of Radiology (X.J.Z.), Neurosurgery (X.J.Z.), and Bioengineering (Z.Z., M.M.K., X.J.Z.), University of Illinois at Chicago, 2242 W Harrison St, Suite 103, Chicago, IL 60612; Department of Neurological Sciences, Rush University Medical Center, Professional Building, Chicago, Ill (D.M., J.G.G.); and Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China (J.Z.)
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Karaman MM, Zhou XJ. A fractional motion diffusion model for a twice-refocused spin-echo pulse sequence. NMR IN BIOMEDICINE 2018; 31:e3960. [PMID: 30133769 DOI: 10.1002/nbm.3960] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 05/14/2018] [Accepted: 05/20/2018] [Indexed: 06/08/2023]
Abstract
The purpose of this study was to develop an analytical expression for a fractional motion (FM) diffusion model to characterize diffusion-induced signal attenuation in a twice-refocused spin-echo (TRSE) sequence that is resilient to eddy currents, and to demonstrate its applicability to human brain imaging in vivo. Based on the FM theory, which provides a unified statistical description for Langevin motions, the diffusion-weighted (DW) MR signal was measured with a TRSE sequence that balances the concomitant gradients. The analytical expression was fitted to a set of DW images acquired with 14 b-values (0-4000 s/mm2 ) from a total of 10 healthy human subjects at 3 T, yielding three FM parameter maps based on anomalous diffusion coefficient Dφ, ψ , diffusion increment variance φ, and diffusion correlation ψ, respectively. These parameters were used to characterize different brain regions in gray matter (GM), white matter (WM), and cerebrospinal fluid. The analytical expression for the TRSE-based FM model accurately described diffusion signal attenuation in healthy brain tissues at high b-values. TRSE's robustness against eddy currents was illustrated by comparing results from an expression for a conventional Stejskal-Tanner sequence. The TRSE-based FM model also produced consistent GM-WM contrast (p < 0.01) across all brain regions studied, whereas the consistency was not observed with the Stejskal-Tanner-based FM model. This new analytical expression is expected to enable further investigations to probe tissue structures by exploiting anomalous diffusion properties without being hindered by eddy-current perturbations at high b-values.
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Affiliation(s)
- M Muge Karaman
- Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Xiaohong Joe Zhou
- Center for MR Research, 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
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA
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Tang L, Zhou XJ. Diffusion MRI of cancer: From low to high b-values. J Magn Reson Imaging 2018; 49:23-40. [PMID: 30311988 DOI: 10.1002/jmri.26293] [Citation(s) in RCA: 118] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 12/14/2022] Open
Abstract
Following its success in early detection of cerebral ischemia, diffusion-weighted imaging (DWI) has been increasingly used in cancer diagnosis and treatment evaluation. These applications are propelled by the rapid development of novel diffusion models to extract biologically valuable information from diffusion-weighted MR signals, and significant advances in MR hardware that has enabled image acquisition with high b-values. This article reviews recent technical developments and clinical applications in cancer imaging using DWI, with a special emphasis on high b-value diffusion models. The article is organized in four sections. First, we provide an overview of diffusion models that are relevant to cancer imaging. The model parameters are discussed in relation to three tissue properties-cellularity, vascularity, and microstructures. An emphasis is placed on characterization of microstructural heterogeneity, given its novelty and close relevance to cancer. Second, we illustrate diffusion MR clinical applications in each of the following three categories: 1) cancer detection and diagnosis; 2) cancer grading, staging, and classification; and 3) cancer treatment response prediction and evaluation. Third, we discuss several practical issues, including selection of image acquisition parameters, reproducibility and reliability, motion management, image distortion, etc., that are commonly encountered when applying DWI to cancer in clinical settings. Lastly, we highlight a few ongoing challenges and provide some possible future directions, particularly in the area of establishing standards via well-organized multicenter clinical trials to accelerate clinical translation of advanced DWI techniques to improving cancer care on a large scale. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:23-40.
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Affiliation(s)
- Lei Tang
- Department of Radiology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research, Beijing, China
| | - Xiaohong Joe Zhou
- Center for MR Research and Departments of Radiology, Neurosurgery, and Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA
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Zhang J, Weaver TE, Zhong Z, Nisi RA, Martin KR, Steffen AD, Karaman MM, Zhou XJ. White matter structural differences in OSA patients experiencing residual daytime sleepiness with high CPAP use: a non-Gaussian diffusion MRI study. Sleep Med 2018; 53:51-59. [PMID: 30445240 DOI: 10.1016/j.sleep.2018.09.011] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Revised: 08/19/2018] [Accepted: 09/20/2018] [Indexed: 01/08/2023]
Abstract
OBJECTIVES To investigate factors associated with residual sleepiness in patients who were highly adherent to continuous positive airway pressure (CPAP). Nocturnal inactivity, comorbidities, concomitant medications, and, in particular, white matter (WM) differences using diffusion magnetic resonance imaging (MRI) were explored using a continuous-time random-walk (CTRW) model. METHODS Twenty-seven male patients (30-55 years of age) with obstructive sleep apnea (OSA) received CPAP as the only treatment (CPAP ≥ 6 h/night) for at least 30 days. Based on the Psychomotor Vigilance Task (PVT) results, participants were divided into a non-sleepy group (lapses ≤ 5; n = 18) and a sleepy group (lapses > 5; n = 9). Mean nocturnal inactivity (sleep proxy) was measured using actigraphy for one week. Diffusion-weighted imaging (DWI) with high b-values, as well as diffusion tensor imaging (DTI), was performed on a 3 T MRI scanner. The DWI dataset was analyzed using the CTRW model that yielded three parameters: temporal diffusion heterogeneity α, spatial diffusion heterogeneity β, and an anomalous diffusion coefficient Dm. The differences in α, β, and Dm between the two groups were investigated by a whole-brain analysis using tract-based spatial statistics (TBSS), followed by a regional analysis on individual fiber tracts using a standard parcellation template. Results from the CTRW model were compared with those obtained from DTI. The three CTRW parameters were also correlated with the clinical assessment scores, Epworth Sleepiness Scale (ESS), PVT lapses, and PVT mean reaction time (MRT) in specific fiber tracts. RESULTS There were no differences between groups in mean sleep duration, comorbidities, and the number or type of medications, including alerting and sedating medications. In the whole-brain DWI analysis, the sleepy group showed higher α (17.27% of the WM voxels) and Dm (17.14%) when compared to the non-sleepy group (P < 0.05), whereas no significant difference in β was observed. In the regional fiber analysis, the sleepy and non-sleepy groups showed significant differences in α, β, or their combinations in a total of 12 fiber tracts; whereas similar differences were not observed in DTI parameters, when age was used as a covariate. Additionally, moderate to strong correlations between the CTRW parameters (α, β, or Dm) and the sleepiness assessment scores (ESS, PVT lapses, or PVT MRT) were observed in specific fiber tracts (|R| = 0.448-0.654, P = 0.0003-0.019). CONCLUSIONS The observed differences in the CTRW parameters between the two groups indicate that WM alterations can be a possible mechanism to explain reversible versus residual sleepiness observed in OSA patients with identical high level of CPAP use. The moderate to strong correlations between the CTRW parameters and the clinical scores suggest the possibility of developing objective and quantitative imaging markers to complement clinical assessment of OSA patients.
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Affiliation(s)
- Jiaxuan Zhang
- Center for MR Research, University of Illinois, Chicago, IL, USA; Department of Radiology, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China
| | - Terri E Weaver
- Department of Biobehavioral Health Science, University of Illinois, Chicago, IL, USA; Center for Sleep and Health, College of Nursing, University of Illinois, Chicago, IL, USA
| | - Zheng Zhong
- Center for MR Research, University of Illinois, Chicago, IL, USA; Department of Bioengineering, College of Medicine, University of Illinois, Chicago, IL, USA
| | - Robyn A Nisi
- Department of Biobehavioral Health Science, University of Illinois, Chicago, IL, USA
| | - Kelly R Martin
- Department of Biobehavioral Health Science, University of Illinois, Chicago, IL, USA
| | - Alana D Steffen
- Department of Health Systems Science, University of Illinois, Chicago, IL, USA
| | - M Muge Karaman
- Center for MR Research, University of Illinois, Chicago, IL, USA; Department of Bioengineering, College of Medicine, University of Illinois, Chicago, IL, USA
| | - Xiaohong Joe Zhou
- Center for MR Research, University of Illinois, Chicago, IL, USA; Department of Radiology, College of Medicine, University of Illinois, Chicago, IL, USA; Department of Bioengineering, College of Medicine, University of Illinois, Chicago, IL, USA; Department of Neurosurgery, College of Medicine, University of Illinois, Chicago, IL, USA.
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Tang L, Li J, Li ZY, Li XT, Gong JF, Ji JF, Sun YS, Shen L. MRI in predicting the response of gastrointestinal stromal tumor to targeted therapy: a patient-based multi-parameter study. BMC Cancer 2018; 18:811. [PMID: 30103713 PMCID: PMC6088415 DOI: 10.1186/s12885-018-4606-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 06/18/2018] [Indexed: 01/28/2023] Open
Abstract
Background To investigate the performance of quantitative indicators of MRI in early prediction of the response of gastrointestinal stromal tumor (GIST) to targeted therapy in a patient-based study. Methods MRI examinations were performed on 62 patients with GIST using 1.5 T scanners before and at two and 12 weeks after treatment with targeted agents. The longest diameter (LD) and contrast-to-noise ratio (CNR) of the tumors were measured by T2-weighted imaging (T2WI), and the apparent diffusion coefficient (ADC) was determined using diffusion-weighted imaging (DWI). The pre-therapy and early percentage changes (%Δ) of the three parameters were compared with regard to their abilities to differentiate responder and non- responder patients, using ROC curves. Results There were 42 patients in responder and 20 in non-responder group. After two weeks of therapy, the percentage changes in the ADC and LD were significantly different between the two groups (ADC: responder 30% vs. non- responder 1%, Z = − 4.819, P < 0.001; LD: responder − 7% vs. non- responder − 2%, Z = − 3.238, P = 0.001), but not in T2WI-CNR (responder − 3% vs. non-responder 9%, Z = − 0.663, P = 0.508). The AUCs on ROC for %ΔLD, %ΔT2WI-CNR and %ΔADC after two weeks of therapy were 0.756, 0.552 and 0.881, respectively, for response differentiation. When %ΔADC ≥15% was used to predict responder, the PPV was 93.3%. Conclusions The percentage change of the ADC after two weeks of therapy outperformed T2WI-CNR and longest diameter in predicting the early response of GIST to targeted therapy.
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Affiliation(s)
- Lei Tang
- Department of Radiology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No. 52Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Jian Li
- Department of Gastroenterology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No.52 Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Zi-Yu Li
- Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No.52Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Xiao-Ting Li
- Department of Radiology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No. 52Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Ji-Fang Gong
- Department of Gastroenterology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No.52 Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Jia-Fu Ji
- Department of Gastrointestinal Surgery, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No.52Fu Cheng Road, HaiDian District, Beijing, 100142, China
| | - Ying-Shi Sun
- Department of Radiology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No. 52Fu Cheng Road, HaiDian District, Beijing, 100142, China.
| | - Lin Shen
- Department of Gastroenterology, Peking University Cancer Hospital & Institute, Key laboratory of Carcinogenesis and Translational Research (Ministry of Education), No.52 Fu Cheng Road, HaiDian District, Beijing, 100142, China.
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