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Wang ZH, Zhu L, Xue HD, Jin ZY. Quantitative MR imaging biomarkers for distinguishing inflammatory pancreatic mass and pancreatic cancer-a systematic review and meta-analysis. Eur Radiol 2024:10.1007/s00330-024-10720-9. [PMID: 38639911 DOI: 10.1007/s00330-024-10720-9] [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: 10/12/2023] [Revised: 02/09/2024] [Accepted: 03/14/2024] [Indexed: 04/20/2024]
Abstract
OBJECTIVES To evaluate the diagnostic performance of quantitative magnetic resonance (MR) imaging biomarkers in distinguishing between inflammatory pancreatic masses (IPM) and pancreatic cancer (PC). METHODS A literature search was conducted using PubMed, Embase, the Cochrane Library, and Web of Science through August 2023. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to evaluate the risk of bias and applicability of the studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated using the DerSimonian-Laird method. Univariate meta-regression analysis was used to identify the potential factors of heterogeneity. RESULTS Twenty-four studies were included in this meta-analysis. The two main types of IPM, mass-forming pancreatitis (MFP) and autoimmune pancreatitis (AIP), differ in their apparent diffusion coefficient (ADC) values. Compared with PC, the ADC value was higher in MFP but lower in AIP. The pooled sensitivity/specificity of ADC were 0.80/0.85 for distinguishing MFP from PC and 0.82/0.84 for distinguishing AIP from PC. The pooled sensitivity/specificity for the maximal diameter of the upstream main pancreatic duct (dMPD) was 0.86/0.74, with a cutoff of dMPD ≤ 4 mm, and 0.97/0.52, with a cutoff of dMPD ≤ 5 mm. The pooled sensitivity/specificity for perfusion fraction (f) was 0.82/0.68, and 0.82/0.77 for mass stiffness values. CONCLUSIONS Quantitative MR imaging biomarkers are useful in distinguishing between IPM and PC. ADC values differ between MFP and AIP, and they should be separated for consideration in future studies. CLINICAL RELEVANCE STATEMENT Quantitative MR parameters could serve as non-invasive imaging biomarkers for differentiating malignant pancreatic neoplasms from inflammatory masses of the pancreas, and hence help to avoid unnecessary surgery. KEY POINTS • Several quantitative MR imaging biomarkers performed well in differential diagnosis between inflammatory pancreatic mass and pancreatic cancer. • The ADC value could discern pancreatic cancer from mass-forming pancreatitis or autoimmune pancreatitis, if the two inflammatory mass types are not combined. • The diameter of main pancreatic duct had the highest specificity for differentiating autoimmune pancreatitis from pancreatic cancer.
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Affiliation(s)
- Zi-He Wang
- School of Medicine, Anhui Medical University, Hefei, China
| | - Liang Zhu
- Department of Radiology, Peking Union Medical College Hospital, Shuaifuyuan No. 1, Dongcheng District, Beijing, 100730, China.
| | - Hua-Dan Xue
- Department of Radiology, Peking Union Medical College Hospital, Shuaifuyuan No. 1, Dongcheng District, Beijing, 100730, China.
| | - Zheng-Yu Jin
- Department of Radiology, Peking Union Medical College Hospital, Shuaifuyuan No. 1, Dongcheng District, Beijing, 100730, China
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Hu R, Zeng GF, Fang Y, Nie L, Liang HL, Wang ZG, Yang H. Intravoxel incoherent motion diffusion-weighted imaging for evaluating the pancreatic perfusion in cirrhotic patients. Abdom Radiol (NY) 2024; 49:492-500. [PMID: 38052890 DOI: 10.1007/s00261-023-04063-0] [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: 04/17/2023] [Revised: 09/11/2023] [Accepted: 09/13/2023] [Indexed: 12/07/2023]
Abstract
PURPOSE To assess the characteristics of pancreatic perfusion in normal pancreas versus cirrhotic patients using intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI). METHODS A total of 67 cirrhotic patients and 33 healthy subjects underwent IVIM on a 3.0 T MRI scanner. Diffusion coefficient (ADCslow), pseudo-diffusion coefficient (ADCfast), and perfusion fraction (f) were calculated based on the bi-exponential model. The pancreatic IVIM-derived parameters were then compared. In the cirrhotic group, the relationship was analyzed between IVIM-derived pancreatic parameters and different classes of hepatic function as determined by the Child-Pugh classification. Also, the pancreatic IVIM-derived parameters were compared among different classes of cirrhosis as determined by the Child-Pugh classification. RESULTS The f value of the pancreas in cirrhotic patients was significantly lower than that in normal subjects (p = 0.01). In the cirrhotic group, the f value of the pancreas decreased with the increase of the Child-Pugh classification (R = - 0.49, p = 0.00). The f value of the pancreas was significantly higher in Child-Pugh class A patients than in class B and C patients (p = 0.02, 0.00, respectively), whereas there was no significant difference between class B and C patients (p = 0.16). CONCLUSION The IVIM-derived perfusion-related parameter (f value) could be helpful for the evaluation of pancreatic perfusion in liver cirrhosis. Our data also suggest that the blood perfusion decrease in the pancreas is present in liver cirrhosis, and the pancreatic perfusion tends to decrease with the increasing severity of hepatic function. TRIAL REGISTRATION Trial registration number is 2021-ky-68 and date of registration for prospectively registered trials is February 23, 2022.
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Affiliation(s)
- Ran Hu
- Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, No.6, Panxi 7th Road, Jiangbei District, Chongqing, 400021, People's Republic of China
| | - Guo-Fei Zeng
- Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, No.6, Panxi 7th Road, Jiangbei District, Chongqing, 400021, People's Republic of China
| | - Yu Fang
- Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, No.6, Panxi 7th Road, Jiangbei District, Chongqing, 400021, People's Republic of China
| | - Lisha Nie
- GE Healthcare, MR Research China, Beijing, People's Republic of China
| | - Hui-Lou Liang
- GE Healthcare, MR Research China, Beijing, People's Republic of China
| | - Zhi-Gang Wang
- Department of Ultrasound, The Second Affiliated Hospital of Chongqing Medical University, 76 Linjiang Road, Yuzhong Distinct, Chongqing, 400010, People's Republic of China.
| | - Hua Yang
- Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, No.6, Panxi 7th Road, Jiangbei District, Chongqing, 400021, People's Republic of China.
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Rauh SS, Maier O, Gurney-Champion OJ, Hooijmans MT, Stollberger R, Nederveen AJ, Strijkers GJ. Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations. NMR IN BIOMEDICINE 2023:e4927. [PMID: 36932842 DOI: 10.1002/nbm.4927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 01/16/2023] [Accepted: 03/06/2023] [Indexed: 06/18/2023]
Abstract
Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.
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Affiliation(s)
- Susanne S Rauh
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Oliver Maier
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
| | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam Movement Sciences, University of Amsterdam, The Netherlands
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Pancreatic Mass Characterization Using IVIM-DKI MRI and Machine Learning-Based Multi-Parametric Texture Analysis. Bioengineering (Basel) 2023; 10:bioengineering10010083. [PMID: 36671655 PMCID: PMC9854749 DOI: 10.3390/bioengineering10010083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 01/04/2023] [Indexed: 01/11/2023] Open
Abstract
Non-invasive characterization of pancreatic masses aids in the management of pancreatic lesions. Intravoxel incoherent motion-diffusion kurtosis imaging (IVIM-DKI) and machine learning-based texture analysis was used to differentiate pancreatic masses such as pancreatic ductal adenocarcinoma (PDAC), pancreatic neuroendocrine tumor (pNET), solid pseudopapillary epithelial neoplasm (SPEN), and mass-forming chronic pancreatitis (MFCP). A total of forty-eight biopsy-proven patients with pancreatic masses were recruited and classified into pNET (n = 13), MFCP (n = 6), SPEN (n = 4), and PDAC (n = 25) groups. All patients were scanned for IVIM-DKI sequences acquired with 14 b-values (0 to 2500 s/mm2) on a 1.5T MRI. An IVIM-DKI model with a 3D total variation (TV) penalty function was implemented to estimate the precise IVIM-DKI parametric maps. Texture analysis (TA) of the apparent diffusion coefficient (ADC) and IVIM-DKI parametric map was performed and reduced using the chi-square test. These features were fed to an artificial neural network (ANN) for characterization of pancreatic mass subtypes and validated by 5-fold cross-validation. Receiver operator characteristics (ROC) analyses were used to compute the area under curve (AUC). Perfusion fraction (f) was significantly higher (p < 0.05) in pNET than PDAC. The f showed better diagnostic performance for PDAC vs. MFCP with AUC:0.77. Both pseudo-diffusion coefficient (D*) and f for PDAC vs. pNET showed an AUC of 0.73. ADC and diffusion coefficient (D) showed good diagnostic performance for pNET vs. MFCP with AUC: 0.79 and 0.76, respectively. In the TA of PDAC vs. non-PDAC, f and combined IVIM-DKI parameters showed high accuracy ≥ 84.3% and AUC ≥ 0.84. Mean f and combined IVIM-DKI parameters estimated that the IVIM-DKI model with TV texture features has the potential to be helpful in characterizing pancreatic masses.
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Wang L, Scott FI, Boursi B, Reiss KA, Williams S, Glick H, Yang YX. Cost-Effectiveness of a Risk-Tailored Pancreatic Cancer Early Detection Strategy Among Patients With New-Onset Diabetes. Clin Gastroenterol Hepatol 2022; 20:1997-2004.e7. [PMID: 34737092 DOI: 10.1016/j.cgh.2021.10.037] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 08/16/2021] [Accepted: 10/24/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND & AIMS Screening for pancreatic ductal adenocarcinoma (PDAC) in asymptomatic adults is not recommended, however, patients with new-onset diabetes (NoD) have an 8 times higher risk of PDAC than expected. A novel risk-tailored early detection strategy targeting high-risk NoD patients might improve PDAC prognosis. We sought to evaluate the cost effectiveness of this strategy. METHODS We compared PDAC early detection strategies targeting NoD individuals age 50 years and older at various minimal predicted PDAC risk thresholds vs standard of care in a Markov state-transition decision model under the health care sector perspective using a lifetime horizon. RESULTS At a willingness to pay (WTP) threshold of $150,000 per quality-adjusted life-year, the early detection strategy targeting patients with a minimum predicted 3-year PDAC risk of 1% was cost effective (incremental cost-effectiveness ratio, $116,911). At a WTP threshold of $100,000 per quality-adjusted life-year, the early detection strategy at the 2% risk threshold was cost effective (incremental cost-effectiveness ratio, $63,045). The proportion of PDACs detected at local stage, costs of treatment for metastatic PDAC, utilities of local and regional cancers, and sensitivity of screening were the most influential parameters. Probabilistic sensitivity analysis confirmed that at a WTP threshold of $150,000, early detection at the 1.0% risk threshold was favored (30.6%), followed by the 0.5% risk threshold (20.4%) vs standard of care (1.7%). At a WTP threshold of $100,000, early detection at the 1.0% risk threshold was favored (27.3%) followed by the 2.0% risk threshold (22.8%) vs standard of care (2.0%). CONCLUSIONS A risk-tailored PDAC early detection strategy targeting NoD patients with a minimum predicted 3-year PDAC risk of 1.0% to 2.0% may be cost effective.
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Affiliation(s)
- Louise Wang
- Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Frank I Scott
- Division of Gastroenterology and Hepatology, Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado
| | - Ben Boursi
- Tel-Aviv University, Tel-Aviv, Israel; Department of Oncology, Sheba Medical Center, Tel-Hashomer, Israel; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Kim A Reiss
- Division of Hematology and Oncology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Sankey Williams
- Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Henry Glick
- Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Yu-Xiao Yang
- Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.
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Sen S, Valindria V, Slator PJ, Pye H, Grey A, Freeman A, Moore C, Whitaker H, Punwani S, Singh S, Panagiotaki E. Differentiating False Positive Lesions from Clinically Significant Cancer and Normal Prostate Tissue Using VERDICT MRI and Other Diffusion Models. Diagnostics (Basel) 2022; 12:1631. [PMID: 35885536 PMCID: PMC9319485 DOI: 10.3390/diagnostics12071631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 06/29/2022] [Accepted: 07/02/2022] [Indexed: 11/16/2022] Open
Abstract
False positives on multiparametric MRIs (mp-MRIs) result in many unnecessary invasive biopsies in men with clinically insignificant diseases. This study investigated whether quantitative diffusion MRI could differentiate between false positives, true positives and normal tissue non-invasively. Thirty-eight patients underwent mp-MRI and Vascular, Extracellular and Restricted Diffusion for Cytometry in Tumors (VERDICT) MRI, followed by transperineal biopsy. The patients were categorized into two groups following biopsy: (1) significant cancer—true positive, 19 patients; (2) atrophy/inflammation/high-grade prostatic intraepithelial neoplasia (PIN)—false positive, 19 patients. The clinical apparent diffusion coefficient (ADC) values were obtained, and the intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI) and VERDICT models were fitted via deep learning. Significant differences (p < 0.05) between true positive and false positive lesions were found in ADC, IVIM perfusion fraction (f) and diffusivity (D), DKI diffusivity (DK) (p < 0.0001) and kurtosis (K) and VERDICT intracellular volume fraction (fIC), extracellular−extravascular volume fraction (fEES) and diffusivity (dEES) values. Significant differences between false positives and normal tissue were found for the VERDICT fIC (p = 0.004) and IVIM D. These results demonstrate that model-based diffusion MRI could reduce unnecessary biopsies occurring due to false positive prostate lesions and shows promising sensitivity to benign diseases.
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Affiliation(s)
- Snigdha Sen
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Vanya Valindria
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Paddy J. Slator
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
| | - Hayley Pye
- Molecular Diagnostics and Therapeutics Group, University College London, London WC1E 6BT, UK; (H.P.); (H.W.)
| | - Alistair Grey
- Department of Urology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK; (A.G.); (C.M.)
| | - Alex Freeman
- Department of Pathology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK;
| | - Caroline Moore
- Department of Urology, University College London Hospitals NHS Foundations Trust, London NW1 2PG, UK; (A.G.); (C.M.)
| | - Hayley Whitaker
- Molecular Diagnostics and Therapeutics Group, University College London, London WC1E 6BT, UK; (H.P.); (H.W.)
| | - Shonit Punwani
- Centre for Medical Imaging, University College London, London WC1E 6BT, UK; (S.P.); (S.S.)
| | - Saurabh Singh
- Centre for Medical Imaging, University College London, London WC1E 6BT, UK; (S.P.); (S.S.)
| | - Eleftheria Panagiotaki
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1E 6BT, UK; (S.S.); (V.V.); (P.J.S.)
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Li HH, Sun B, Tan C, Li R, Fu CX, Grimm R, Zhu H, Peng WJ. The Value of Whole-Tumor Histogram and Texture Analysis Using Intravoxel Incoherent Motion in Differentiating Pathologic Subtypes of Locally Advanced Gastric Cancer. Front Oncol 2022; 12:821586. [PMID: 35223503 PMCID: PMC8864172 DOI: 10.3389/fonc.2022.821586] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 01/20/2022] [Indexed: 01/02/2023] Open
Abstract
Purpose To determine if whole-tumor histogram and texture analyses using intravoxel incoherent motion (IVIM) parameters values could differentiate the pathologic characteristics of locally advanced gastric cancer. Methods Eighty patients with histologically confirmed locally advanced gastric cancer who received surgery in our institution were retrospectively enrolled into our study between April 2017 and December 2018. Patients were excluded if they had lesions with the smallest diameter < 5 mm and severe image artifacts. MR scanning included IVIM sequences (9 b values, 0, 20, 40, 60, 100, 150,200, 500, and 800 s/mm2) used in all patients before treatment. Whole tumors were segmented by manually drawing the lesion contours on each slice of the diffusion-weighted imaging (DWI) images (with b=800). Histogram and texture metrics for IVIM parameters values and apparent diffusion coefficient (ADC) values were measured based on whole-tumor volume analyses. Then, all 24 extracted metrics were compared between well, moderately, and poorly differentiated tumors, and between different Lauren classifications, signet-ring cell carcinomas, and other poorly cohesive carcinomas using univariate analyses. Multivariate logistic analyses and multicollinear tests were used to identify independent influencing factors from the significant variables of the univariate analyses to distinguish tumor differentiation and Lauren classifications. ROC curve analyses were performed to evaluate the diagnostic performance of these independent influencing factors for determining tumor differentiation and Lauren classifications and identifying signet-ring cell carcinomas. The interobserver agreement was also conducted between the two observers for image quality evaluations and parameter metric measurements. Results For diagnosing tumor differentiation, the ADCmedian, pure diffusion coefficient median (Dslowmedian), and pure diffusion coefficient entropy (Dslowentropy) showed the greatest AUCs: 0.937, 0.948, and 0.850, respectively, and no differences were found between the three metrics, P>0.05). The 95th percentile perfusion factor (FP P95th) was the best metric to distinguish diffuse-type GCs vs. intestinal/mixed (AUC=0.896). The ROC curve to distinguish signet-ring cell carcinomas from other poorly cohesive carcinomas showed that the Dslowmedian had AUC of 0.738. For interobserver reliability, image quality evaluations showed excellent agreement (interclass correlation coefficient [ICC]=0.85); metrics measurements of all parameters indicated good to excellent agreement (ICC=0.65-0.89), except for the Dfast metric, which showed moderate agreement (ICC=0.41-0.60). Conclusions The whole-tumor histogram and texture analyses of the IVIM parameters based on the biexponential model provided a non-invasive method to discriminate pathologic tumor subtypes preoperatively in patients with locally advanced gastric cancer. The metric FP P95th derived from IVIM performed better in determining Lauren classifications than the mono-exponential model.
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Affiliation(s)
- Huan-Huan Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Bo Sun
- Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Cong Tan
- Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Rong Li
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Cai-Xia Fu
- MR Applications Development, Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China
| | - Robert Grimm
- MR Applications Development, Siemens Healthcare, Erlangen, Germany
| | - Hui Zhu
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Wei-Jun Peng
- Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China
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Non-Invasive Monitoring of Increased Fibrotic Tissue and Hyaluronan Deposition in the Tumor Microenvironment in the Advanced Stages of Pancreatic Ductal Adenocarcinoma. Cancers (Basel) 2022; 14:cancers14040999. [PMID: 35205746 PMCID: PMC8870395 DOI: 10.3390/cancers14040999] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/06/2022] [Accepted: 02/11/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease with a poor prognosis. A better understanding of the tumor microenvironment may help better treat the disease. Magnetic resonance imaging may be a great tool for monitoring the tumor microenvironment at different stages of tumor evolution. Here, we used multi-parametric magnetic resonance imaging techniques to monitor underlying pathophysiologic processes during the advanced stages of tumor development and correlated with histologic measurements. Abstract Pancreatic ductal adenocarcinomas are characterized by a complex and robust tumor microenvironment (TME) consisting of fibrotic tissue, excessive levels of hyaluronan (HA), and immune cells. We utilized quantitative multi-parametric magnetic resonance imaging (mp-MRI) methods at 14 Tesla in a genetically engineered KPC (KrasLSL-G12D/+, Trp53LSL-R172H/+, Cre) mouse model to assess the complex TME in advanced stages of tumor development. The whole tumor, excluding cystic areas, was selected as the region of interest for data analysis and subsequent statistical analysis. Pearson correlation was used for statistical inference. There was a significant correlation between tumor volume and T2 (r = −0.66), magnetization transfer ratio (MTR) (r = 0.60), apparent diffusion coefficient (ADC) (r = 0.48), and Glycosaminoglycan-chemical exchange saturation transfer (GagCEST) (r = 0.51). A subset of mice was randomly selected for histological analysis. There were positive correlations between tumor volume and fibrosis (0.92), and HA (r = 0.76); GagCEST and HA (r = 0.81); and MTR and CD31 (r = 0.48). We found a negative correlation between ADC low-b (perfusion) and Ki67 (r = −0.82). Strong correlations between mp-MRI and histology results suggest that mp-MRI can be used as a non-invasive tool to monitor the tumor microenvironment.
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Liu J, Hu L, Zhou B, Wu C, Cheng Y. Development and validation of a novel model incorporating MRI-based radiomics signature with clinical biomarkers for distinguishing pancreatic carcinoma from mass-forming chronic pancreatitis. Transl Oncol 2022; 18:101357. [PMID: 35114568 PMCID: PMC8818577 DOI: 10.1016/j.tranon.2022.101357] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/14/2021] [Accepted: 01/24/2022] [Indexed: 12/12/2022] Open
Abstract
A novel model incorporating multiparametric MRI-based radiomic signature with clinically independent risk factors can greatly improve the non-invasive diagnostic accuracy in differentiating PC from MFCP. The nomogram integrating rad-score and clinically independent risk factors had a better diagnostic performance than the mp-MRI and clinical models. The mixed model may aid in formulating treatment strategies and help to avoid unnecessary surgical operations for doctors.
Purpose It is difficult to make a clear differential diagnosis of pancreatic carcinoma (PC) and mass-forming chronic pancreatitis (MFCP) via conventional examinations. We aimed to develop a novel model incorporating an MRI-based radiomics signature with clinical biomarkers for distinguishing the two lesions. Methods A total of 102 patients were retrospectively enrolled and randomly divided into the training and validation cohorts. Radiomics features were extracted from four different sequences. Individual imaging modality radiomics signature, multiparametric MRI (mp-MRI) radiomics signature, and a final mixed model based on mp-MRI and clinically independent risk factors were established to discriminate between PC and MFCP. The diagnostic performance of each model and model discrimination were assessed in both the training and validation cohorts. Results ADC had the best predictive performance among the four individual radiomics models, but there were no significant differences between the pairs of models (all p > 0.05). Six potential radiomics features were finally selected from the 960 texture features to formulate the radiomics score (rad-score) of the mp-MRI model. In addition, the boxplot results of the distributions of rad-scores identified the rad-score as an independent predictive factor for the differentiation of PC and MFCP (p< 0.001). Notably, the nomogram integrating rad-score and clinically independent risk factors had a better diagnostic performance than the mp-MRI and clinical models. These results were further confirmed by the validation group. Conclusion The mixed model was developed and preliminarily validated to distinguish PC from MFCP, which may benefit the formulation of treatment strategies and nonsurgical procedures.
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Affiliation(s)
- Jingjing Liu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China
| | - Lei Hu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China
| | - Bi Zhou
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China.
| | - Chungen Wu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China
| | - Yingsheng Cheng
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, People's Republic of China
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10
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Tavakoli AA, Dreher C, Mlynarska A, Kuder TA, Gnirs R, Schlemmer HP, Bickelhaupt S. Pancreatic imaging using diffusivity mapping - Influence of sequence technique on qualitative and quantitative analysis. Clin Imaging 2021; 83:33-40. [PMID: 34953309 DOI: 10.1016/j.clinimag.2021.11.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 11/08/2021] [Accepted: 11/30/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To compare image quality of an optimized diffusion weighted imaging (DWI) sequence with advanced post-processing and motion correction (advanced-EPI) to a standard DWI protocol (standard-EPI) in pancreatic imaging. MATERIALS AND METHODS 62 consecutive patients underwent abdominal MRI at 1.5 T were included in this retrospective analysis of data collected as part of an IRB approved study. All patients received a standard-EPI and an advanced-EPI DWI with advanced post-processing and motion correction. Two blinded radiologists evaluated the parameters image quality, detail of parenchyma, sharpness of boundaries and discernibility from adjacent structures on b = 900 s/mm2 images using a Likert-like scale. Segmentation of pancreatic head, body and tail were obtained and apparent diffusion coefficient (ADC) was calculated separately for each region. Apparent tissue-to-background ratio (TBR) was calculated at b = 50 s/mm2 and at b = 900 s/mm2. RESULTS The advanced-EPI yielded significantly higher scores for pancreatic parameters of image quality, detail level of parenchyma, sharpness of boundaries and discernibility from adjacent structures in comparison to standard-EPI (p < 0.001 for all, kappa = [0.46,0.71]) and was preferred in 96% of the cases when directly compared. ADC of the pancreas was 7% lower in advanced-EPI (1.236 ± 0.152 vs. 1.146 ± 0.126 μm2/ms, p < 0.001). ADC in the pancreatic tail was significantly lower for both sequences compared to head and body (all p < 0.001). There was comparable TBR for both sequences at b = 50 s/mm2 (standard-EPI: 19.0 ± 5.9 vs. advanced-EPI: 19.0 ± 6.4, p = 0.96), whereas at b = 900 s/mm2, TBR was 51% higher for advanced-EPI (standard-EPI: 7.1 ± 2.5 vs. advanced-EPI: 10.8 ± 5.1, p < 0.001). CONCLUSION An advanced DWI sequence might increase image quality for focused imaging of the pancreas and providing improved parenchymal detail levels compared to a standard DWI.
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Affiliation(s)
- Anoshirwan Andrej Tavakoli
- German Cancer Research Center (DKFZ), Department of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Constantin Dreher
- German Cancer Research Center (DKFZ), Department of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; Department of Radiation Oncology, University Medical Center Mannheim, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany.
| | - Anna Mlynarska
- German Cancer Research Center (DKFZ), Department of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Tristan Anselm Kuder
- German Cancer Research Center (DKFZ), Medical Physics in Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Regula Gnirs
- German Cancer Research Center (DKFZ), Department of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Heinz-Peter Schlemmer
- German Cancer Research Center (DKFZ), Department of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
| | - Sebastian Bickelhaupt
- German Cancer Research Center (DKFZ), Medical Imaging and Radiology - Cancer Prevention, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; University Hospital Erlangen, Institute of Radiology, Maximiliansplatz 3, 91054 Erlangen, Germany.
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11
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Ischemia-Reperfusion Injuries Assessment during Pancreas Preservation. Int J Mol Sci 2021; 22:ijms22105172. [PMID: 34068301 PMCID: PMC8153272 DOI: 10.3390/ijms22105172] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 04/25/2021] [Accepted: 05/10/2021] [Indexed: 12/20/2022] Open
Abstract
Maintaining organ viability between donation and transplantation is of critical importance for optimal graft function and survival. To date in pancreas transplantation, static cold storage (SCS) is the most widely practiced method of organ preservation. The first experiments in ex vivo perfusion of the pancreas were performed at the beginning of the 20th century. These perfusions led to organ oedema, hemorrhage, and venous congestion after revascularization. Despite these early hurdles, a number of factors now favor the use of perfusion during preservation: the encouraging results of HMP in kidney transplantation, the development of new perfusion solutions, and the development of organ perfusion machines for the lung, heart, kidneys and liver. This has led to a resurgence of research in machine perfusion for whole organ pancreas preservation. This review highlights the ischemia-reperfusion injuries assessment during ex vivo pancreas perfusion, both for assessment in pre-clinical experimental models as well for future use in the clinic. We evaluated perfusion dynamics, oedema assessment, especially by impedance analysis and MRI, whole organ oxygen consumption, tissue oxygen tension, metabolite concentrations in tissue and perfusate, mitochondrial respiration, cell death, especially by histology, total cell free DNA, caspase activation, and exocrine and endocrine assessment.
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12
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[The microarchitecture of pancreatic cancer from the point of view of the pathologist and the radiologist]. DER PATHOLOGE 2021; 42:524-529. [PMID: 33956172 PMCID: PMC8390414 DOI: 10.1007/s00292-021-00949-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/26/2021] [Indexed: 11/06/2022]
Abstract
Die diagnostische Radiologie ist gemeinsam mit der diagnostischen Pathologie eines der klinisch-morphologischen Fächer, welche in unterschiedlicher makroskopischer bzw. mikroskopischer Auflösung zur Detektion, Charakterisierung sowie zum Ausbreitungsmuster eines Tumors führen. Die klinischen Disziplinen sind oft voneinander getrennt, wenngleich es vor allem in klinischen Tumorboards immer stärkere Verzahnungen gibt. Am Beispiel des Pankreaskarzinoms sind die Korrelationen radiologischer und pathologischer Diagnostik dargestellt.
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13
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Accuracy of quantitative diffusion-weighted imaging for differentiating benign and malignant pancreatic lesions: a systematic review and meta-analysis. Eur Radiol 2021; 31:7746-7759. [PMID: 33847811 DOI: 10.1007/s00330-021-07880-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 02/19/2021] [Accepted: 03/12/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND A variety of imaging techniques can be used to evaluate diffusion characteristics to differentiate malignant and benign pancreatic lesions. The diagnostic performance of diffusion parameters has not been systematic assessed. PURPOSE We aimed to investigate the diagnostic efficacy of quantitative diffusion-weighted imaging (DWI) for pancreatic lesions. METHODS A literature search was conducted using the PubMed, Embase, and Cochrane Library databases for studies from inception to March 30, 2020, which involves the quantitative diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in the pancreas. Studies were reviewed according to inclusion and exclusion criteria. The quality of articles was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUATAS-2). A bivariate random-effects model was used to evaluate pooled sensitivities and specificities. Univariable meta-regression analysis was used to test the effects of factors that contributed to the heterogeneity. RESULTS A total of 31 studies involving 1558 patients were ultimately eligible for data extraction. The lowest heterogeneity was found in specificity of perfusion fraction (f) with the I2 value was 17.97% and Cochran p value was 0.28. However, high heterogeneities were found for the other parameters (all I2 > 50%). There was no publication bias found in funnel plot (p = 0.30) for the apparent diffusion coefficient (ADC) parameter. The pooled sensitivities for ADC, f, pure diffusion coefficient (D), and pseudo diffusivity coefficient (D*) were 83%, 81%, 76%, and 84%, respectively. The pooled specificities for ADC, f, D, and D* were 87%, 83%, 69%, and 81% respectively. The areas under the curves for ADC, f, D, and D* were 0.92, 0.87, 0.79, and 0.87 respectively. CONCLUSION Quantitative DWI and IVIM have a good diagnostic performance for differentiating malignant and benign pancreatic lesions. KEY POINTS • IVIM has high sensitivity and specificity (84% and 83%, respectively) for differential diagnosis of pancreatic lesions, which is comparable to that of the ADC (83% and 87%, respectively). • The ADC has an excellent diagnostic performance for differentiating malignant from benign IPMNs (sensitivity, 0.83; specificity, 0.92); the f has the best diagnostic performance for differentiating pancreatic carcinoma from PNET (sensitivity, 0.85; specificity, 0.85). • For the ADC, using a maximal b value < 800 s/mm2 has a higher diagnostic accuracy than ≥ 800 s/mm2; performing in a high field strength (3.0 T) system has a higher diagnostic accuracy than a low field strength (1.5 T) for pancreatic lesions.
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14
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Chen J, Liu S, Tang Y, Zhang X, Cao M, Xiao Z, Ren M, Chen X. Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis. Eur J Radiol 2021; 139:109672. [PMID: 33819806 DOI: 10.1016/j.ejrad.2021.109672] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Revised: 03/13/2021] [Accepted: 03/18/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC). METHOD A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed. RESULTS Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I2 = 86 %) and 85 % (95 % CI, 79 %-90 %, I2 = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I2 = 45 %), 88 % (95 % CI, 77 %-94 %, I2 = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I2 = 87 %), 69 % (95 % CI, 52 %-82 %, I2 = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I2 = 79 %), 74 % (95 % CI, 60 %-84 %, I2 = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P<0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P<0.01), and thickness (sensitivity, P<0.01; specificity, P = 0.01) were sources of ADC heterogeneity. CONCLUSIONS DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.
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Affiliation(s)
- Jing Chen
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China.
| | - Shuxue Liu
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Yude Tang
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Xiongbiao Zhang
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Mingming Cao
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Zheng Xiao
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Mingda Ren
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
| | - Xianteng Chen
- Department of Radiology, Zhongshan Affiliated Hospital, Guangzhou University of Traditional Chinese Medicine, Zhongshan, 528400, PR China
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Iima M. Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends. Magn Reson Med Sci 2020; 20:125-138. [PMID: 32536681 PMCID: PMC8203481 DOI: 10.2463/mrms.rev.2019-0124] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine.,Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science (iACT), Kyoto University Hospital
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16
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Granata V, Fusco R, Sansone M, Grassi R, Maio F, Palaia R, Tatangelo F, Botti G, Grimm R, Curley S, Avallone A, Izzo F, Petrillo A. Magnetic resonance imaging in the assessment of pancreatic cancer with quantitative parameter extraction by means of dynamic contrast-enhanced magnetic resonance imaging, diffusion kurtosis imaging and intravoxel incoherent motion diffusion-weighted imaging. Therap Adv Gastroenterol 2020; 13:1756284819885052. [PMID: 32499833 PMCID: PMC7243396 DOI: 10.1177/1756284819885052] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 10/07/2019] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Despite great technical advances in imaging, such as multidetector computed tomography and magnetic resonance imaging (MRI), diagnosing pancreatic solid lesions correctly remains challenging, due to overlapping imaging features with benign lesions. We wanted to evaluate functional MRI to differentiate pancreatic tumors, peritumoral inflammatory tissue, and normal pancreatic parenchyma by means of dynamic contrast-enhanced MRI (DCE-MRI)-, diffusion kurtosis imaging (DKI)-, and intravoxel incoherent motion model (IVIM) diffusion-weighted imaging (DWI)-derived parameters. METHODS We retrospectively analyzed 24 patients, each with histopathological diagnosis of pancreatic tumor, and 24 patients without pancreatic lesions. Functional MRI was acquired using a 1.5 MR scanner. Peritumoral inflammatory tissue was assessed by drawing regions of interest on the tumor contours. DCE-MRI, IVIM and DKI parameters were extracted. Nonparametric tests and receiver operating characteristic (ROC) curves were calculated. RESULTS There were statistically significant differences in median values among the three groups observed by Kruskal-Wallis test for the DKI mean diffusivity (MD), IVIM perfusion fraction (fp) and IVIM tissue pure diffusivity (Dt). MD had the best results to discriminate normal pancreas plus peritumoral inflammatory tissue versus pancreatic tumor, to separate normal pancreatic parenchyma versus pancreatic tumor and to differentiate peritumoral inflammatory tissue versus pancreatic tumor, respectively, with an accuracy of 84%, 78%, 83% and area under ROC curve (AUC) of 0.85, 0.82, 0.89. The findings were statistically significant compared with those of other parameters (p value < 0.05 using McNemar's test). Instead, to discriminate normal pancreas versus peritumoral inflammatory tissue or pancreatic tumor and to differentiate normal pancreatic parenchyma versus peritumoral inflammatory tissue, there were no statistically significant differences between parameters' accuracy (p > 0.05 at McNemar's test). CONCLUSIONS Diffusion parameters, mainly MD by DKI, could be helpful for the differentiation of normal pancreatic parenchyma, perilesional inflammation, and pancreatic tumor.
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Affiliation(s)
- Vincenza Granata
- Radiology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Roberta Fusco
- Department of Radiology, Istituto Nazionale Tumori Fondazione G. Pascale, via Mariano Semmola, Naples 80131, Italy
| | - Mario Sansone
- Department of Electrical Engineering and Information Technologies (DIETI), University of Naples Federico II, Naples, Italy
| | - Roberto Grassi
- Radiology Unit, Università della Campania Luigi Vanvitelli, Naples, Italy
| | - Francesca Maio
- Radiology Unit, University of Naples Federico II, Naples, Italy
| | - Raffaele Palaia
- Hepatobiliary Surgical Oncology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Fabiana Tatangelo
- Diagnostic Pathology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Gerardo Botti
- Diagnostic Pathology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Robert Grimm
- Siemens Healthcare GmbH, Erlangen, Bayern, Germany
| | - Steven Curley
- Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - Antonio Avallone
- Abdominal Oncology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Francesco Izzo
- Hepatobiliary Surgical Oncology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
| | - Antonella Petrillo
- Radiology Unit, ‘Istituto Nazionale Tumori – IRCCS – Fondazione G. Pascale’, Naples, Italy
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Ogura A, Sotome H, Asai A, Fuju A. Evaluation of capillary blood volume in the lower limb muscles after exercise by intravoxel incoherent motion. Radiol Med 2020; 125:474-480. [DOI: 10.1007/s11547-020-01163-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 03/02/2020] [Indexed: 12/22/2022]
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18
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Tokunaga K, Arizono S, Shimizu H, Fujimoto K, Kurata M, Minamiguchi S, Isoda H, Togashi K. Optimizing b-values for accurate depiction of pancreatic cancer with tumor-associated pancreatitis on computed diffusion-weighted imaging. Clin Imaging 2020; 61:20-26. [PMID: 31954347 DOI: 10.1016/j.clinimag.2020.01.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 12/05/2019] [Accepted: 01/07/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE To determine the optimal b-value for accurate depiction of pancreatic cancer (PC) in patients with active tumor-associated pancreatitis (TAP), using computed diffusion-weighted imaging (cDWI) with a range of b-values up to 3000 s/mm2. METHODS The study protocol was approved by the institutional review board. We retrospectively analyzed 34 consecutive PC cases with active TAP who underwent pancreatectomy without preoperative therapy. Four cDWI datasets with b-values of 1500-3000 s/mm2 (cDWI1500-cDWI3000) were generated from the original DWI datasets with b-values of 0 and 1000 s/mm2 obtained using a 3-T scanner. Two board-certified radiologists evaluated images qualitatively (tumor conspicuity and total image quality), and another two board-certified radiologists placed regions of interest for quantitative evaluations (apparent diffusion coefficient [ADC] values of both lesions, contrast ratio [CR] of PC to active TAP, and volume ratio [VR] of PC to surgical specimen). RESULTS As the b-value increased, tumor conspicuity improved significantly in cDWI2000 and cDWI2500 (P = 0.0121 and 0.0015, respectively), although total image quality decreased in all cDWIs compared with DWI1000 (P < 0.0001). Significantly lower ADC values were seen in PC (P < 0.0001). All cDWI groups showed positive correlation between the tumor conspicuity and ADC difference between PC and TAP. CR increased with the b-value, while VR decreased. Significant equivalence of VR to the surgical specimen was seen on cDWI2000 (P = 0.0031). CONCLUSION Accurate depiction of PC was optimal with cDWI2000 in the presence of active TAP.
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Affiliation(s)
- Koji Tokunaga
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Shigeki Arizono
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Hironori Shimizu
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Koji Fujimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Mariyo Kurata
- Department of Diagnostic Pathology, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Sachiko Minamiguchi
- Department of Diagnostic Pathology, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Hiroyoshi Isoda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan.
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Ren S, Zhang J, Chen J, Cui W, Zhao R, Qiu W, Duan S, Chen R, Chen X, Wang Z. Evaluation of Texture Analysis for the Differential Diagnosis of Mass-Forming Pancreatitis From Pancreatic Ductal Adenocarcinoma on Contrast-Enhanced CT Images. Front Oncol 2019; 9:1171. [PMID: 31750254 PMCID: PMC6848378 DOI: 10.3389/fonc.2019.01171] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 10/18/2019] [Indexed: 12/13/2022] Open
Abstract
Purpose: To investigate the potential of computed tomography (CT) imaging features and texture analysis to differentiate between mass-forming pancreatitis (MFP) and pancreatic ductal adenocarcinoma (PDAC). Materials and Methods: Thirty patients with pathologically proved MFP and 79 patients with PDAC were included in this study. Clinical data and CT imaging features of the two lesions were evaluated. Texture features were extracted from arterial and portal phase CT images using commercially available software (AnalysisKit). Multivariate logistic regression analyses were used to identify relevant CT imaging and texture parameters to discriminate MFP from PDAC. Receiver operating characteristic curves were performed to determine the diagnostic performance of predictions. Results: MFP showed a larger size compared to PDAC (p = 0.009). Cystic degeneration, pancreatic ductal dilatation, vascular invasion, and pancreatic sinistral portal hypertension were more frequent and duct penetrating sign was less frequent in PDAC compared to MFP. Arterial CT attenuation, arterial, and portal enhancement ratios of MFP were higher than PDAC (p < 0.05). In multivariate analysis, arterial CT attenuation and pancreatic duct penetrating sign were independent predictors. Texture features in arterial phase including SurfaceArea, Percentile40, InverseDifferenceMoment_angle90_offset4, LongRunEmphasis_angle45_offset4, and uniformity were independent predictors. Texture features in portal phase including LongRunEmphasis_angle135_offset7, VoxelValueSum, LongRunEmphasis_angle135_offset4, and GLCMEntropy_angle45_offset1 were independent predictors. Areas under the curve of imaging feature-based, texture feature-based in arterial and portal phases, and the combined models were 0.84, 0.96, 0.93, and 0.98, respectively. Conclusions: CT texture analysis demonstrates great potential to differentiate MFP from PDAC.
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Affiliation(s)
- Shuai Ren
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Jingjing Zhang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Jingya Chen
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Wenjing Cui
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Rui Zhao
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Wenli Qiu
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | | | - Rong Chen
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Xiao Chen
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
| | - Zhongqiu Wang
- Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China
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Wu D, Zhang J. Evidence of the diffusion time dependence of intravoxel incoherent motion in the brain. Magn Reson Med 2019; 82:2225-2235. [PMID: 31267578 DOI: 10.1002/mrm.27879] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 05/31/2019] [Accepted: 06/01/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE To investigate the diffusion time (TD ) dependence of intravoxel incoherent motion (IVIM) signals in the brain. METHODS A 3-compartment IVIM model was proposed to characterize 2 types of microcirculatory flows in addition to tissue water in the brain: flows that cross multiple vascular segments (pseudo-diffusive) and flows that stay in 1 segment (ballistic) within TD . The model was first evaluated using simulated flow signals. Experimentally, flow-compensated (FC) pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE) sequences were tested using a flow phantom and then used to examine IVIM signals in the mouse brain with TD ranging from ~2.5 ms to 40 ms on an 11.7T scanner. RESULTS By fitting the model to simulated flow signals, we demonstrated the TD dependency of the estimated fraction of pseudo-diffusive flow and the pseudo-diffusion coefficient (D*), which were dictated by the characteristic timescale of microcirculatory flow (τ). Flow phantom experiments validated that the OGSE and FC-PGSE sequences were not susceptible to the change in flow velocity. In vivo mouse brain data showed that both the estimated fraction of pseudo-diffusive flow and D* increased significantly as TD increased. CONCLUSION We demonstrated that IVIM signals measured in the brain are TD -dependent, potentially because more microcirculatory flows approach the pseudo-diffusive limit as TD increases with respect to τ. Measuring the TD dependency of IVIM signals may provide additional information on microvascular flows in the brain.
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Affiliation(s)
- Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Jiangyang Zhang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York
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21
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Chouhan MD, Firmin L, Read S, Amin Z, Taylor SA. Quantitative pancreatic MRI: a pathology-based review. Br J Radiol 2019; 92:20180941. [PMID: 30982337 DOI: 10.1259/bjr.20180941] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
MRI plays an important role in the clinical management of pancreatic disorders and interpretation is reliant on qualitative assessment of anatomy. Conventional sequences capturing pancreatic structure can however be adapted to yield quantitative measures which provide more diagnostic information, with a view to increasing diagnostic accuracy, improving patient stratification, providing robust non-invasive outcome measures for therapeutic trials and ultimately personalizing patient care. In this review, we evaluate the use of established techniques such as secretin-enhanced MR cholangiopancreatography, diffusion-weighted imaging, T 1, T 2* and fat fraction mapping, but also more experimental methods such as MR elastography and arterial spin labelling, and their application to the assessment of diffuse pancreatic disease (including chronic, acute and autoimmune pancreatitis/IgG4 disease, metabolic disease and iron deposition disorders) and cystic/solid focal pancreatic masses. Finally, we explore some of the broader challenges to their implementation and future directions in this promising area.
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Affiliation(s)
- Manil D Chouhan
- 1 University College London (UCL) Centre for Medical Imaging, Division of Medicine, UCL , London , UK.,2 Department of Imaging, University College London Hospitals (UCLH) NHS Foundation Trust , London , UK
| | - Louisa Firmin
- 2 Department of Imaging, University College London Hospitals (UCLH) NHS Foundation Trust , London , UK
| | - Samantha Read
- 2 Department of Imaging, University College London Hospitals (UCLH) NHS Foundation Trust , London , UK
| | - Zahir Amin
- 2 Department of Imaging, University College London Hospitals (UCLH) NHS Foundation Trust , London , UK
| | - Stuart A Taylor
- 1 University College London (UCL) Centre for Medical Imaging, Division of Medicine, UCL , London , UK.,2 Department of Imaging, University College London Hospitals (UCLH) NHS Foundation Trust , London , UK
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Siddiqui N, Vendrami CL, Chatterjee A, Miller FH. Advanced MR Imaging Techniques for Pancreas Imaging. Magn Reson Imaging Clin N Am 2019; 26:323-344. [PMID: 30376973 DOI: 10.1016/j.mric.2018.03.002] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Advances in MR imaging with optimization of hardware, software, and techniques have allowed for an increased role of MR in the identification and characterization of pancreatic disorders. Diffusion-weighted imaging improves the detection and staging of pancreatic neoplasms and aides in the evaluation of acute, chronic and autoimmune pancreatitis. The use of secretin-enhanced MR cholangiography improves the detection of morphologic ductal anomalies, and assists in the characterization of pancreatic cystic lesions and evaluation of acute and chronic pancreatitis. Emerging MR techniques such as MR perfusion, T1 mapping/relaxometry, and MR elastography show promise in further evaluating pancreatic diseases.
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Affiliation(s)
- Nasir Siddiqui
- Department of Radiology, DuPage Medical Group, 430 Warrenville Road, Lisle, IL 60532, USA
| | - Camila Lopes Vendrami
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA
| | - Argha Chatterjee
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA
| | - Frank H Miller
- Department of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, 676 North St. Clair Street Suite 800, Chicago, IL 60611, USA.
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Intravoxel incoherent motion diffusion-weighted MR imaging of solid pancreatic masses: reliability and usefulness for characterization. Abdom Radiol (NY) 2019; 44:131-139. [PMID: 29951899 DOI: 10.1007/s00261-018-1684-z] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE IVIM-DW imaging has shown potential usefulness in the study of pancreatic lesions. Controversial results are available regarding the reliability of the measurements of IVIM-derived parameters. The aim of this study was to evaluate the reliability and the diagnostic potential of IVIM-derived parameters in differentiation among focal solid pancreatic lesions and normal pancreas (NP). METHODS Fifty-seven patients (34 carcinomas-PDACs, 18 neuroendocrine neoplasms-panNENs, and 5 autoimmune pancreatitis-AIP) and 50 subjects with NP underwent 1.5-T MR imaging including IVIM-DWI. Images were analyzed by two independent readers. Apparent diffusion coefficient (ADC), slow component of diffusion (D), incoherent microcirculation (Dp), and perfusion fraction (f) were calculated. Interobserver reliability was assessed with intraclass correlation coefficient (ICC). A Kruskal-Wallis H test with Steel-Dwass post hoc test was used for comparison. The diagnostic performance of each parameter was evaluated through receiver operating characteristic (ROC) curve analysis. RESULTS Overall interobserver agreement was excellent (ICC = 0.860, 0.937, 0.968, and 0.983 for ADC, D, Dp, and f). D, Dp, and f significantly differed among PDACs and panNENs (p = 0.002, < 0.001, and < 0.001), albeit without significant difference at the pairwise comparison of ROC curves (p = 0.08-0.74). Perfusion fraction was higher in AIP compared with PDACs (p = 0.024; AUC = 0.735). Dp and f were higher in panNENs compared with AIP (p = 0.029 and 0.023), without differences at ROC analysis (p = 0.07). CONCLUSIONS IVIM-derived parameters have excellent reliability and could help in differentiation among solid pancreatic lesions and NP.
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Baleato-González S, García-Figueiras R, Luna A, Domínguez-Robla M, Vilanova J. Functional imaging in pancreatic disease. RADIOLOGIA 2018. [DOI: 10.1016/j.rxeng.2018.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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25
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Liu Y, Wang M, Ji R, Cang L, Gao F, Shi Y. Differentiation of pancreatic ductal adenocarcinoma from inflammatory mass: added value of magnetic resonance elastography. Clin Radiol 2018; 73:865-872. [DOI: 10.1016/j.crad.2018.05.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Accepted: 05/10/2018] [Indexed: 02/06/2023]
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26
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Baleato-González S, García-Figueiras R, Luna A, Domínguez-Robla M, Vilanova JC. Functional imaging in pancreatic disease. RADIOLOGIA 2018; 60:451-464. [PMID: 30236460 DOI: 10.1016/j.rx.2018.07.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 07/19/2018] [Accepted: 07/23/2018] [Indexed: 12/12/2022]
Abstract
In addition to the classical morphological evaluation of pancreatic disease, the constant technological advances in imaging techniques based fundamentally on computed tomography and magnetic resonance imaging have enabled the quantitative functional and molecular evaluation of this organ. In many cases, this imaging-based information results in substantial changes to patient management and can be a fundamental tool for the development of biomarkers. The aim of this article is to review the role of emerging functional and molecular techniques based on computed tomography and magnetic resonance imaging in the evaluation of pancreatic disease.
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Affiliation(s)
- S Baleato-González
- Departamento de Radiología, Complexo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela, A Coruña, España.
| | - R García-Figueiras
- Departamento de Radiología, Complexo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela, A Coruña, España
| | - A Luna
- Grupo Health Time. Director - Advanced Medical Imaging, Sercosa (Servicio de Radiología Computerizada), Clínica Las Nieves, Jaén, España
| | - M Domínguez-Robla
- Departamento de Radiología, Complexo Hospitalario Universitario de Santiago de Compostela, Santiago de Compostela, A Coruña, España
| | - J C Vilanova
- Departamento de Radiología, Clínica Girona-Hospital Santa Caterina, Girona, España
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Abstract
Computed tomography is the first-line imaging modality for suspected pancreatic cancer. Magnetic resonance cholangiopancreatography is a second-line modality for suspected pancreatic cancer and is usually reserved for equivocal cases. Both computed tomography and MR are highly sensitive in the detection of pancreatic cancer, with up to 96% and 93.5% sensitivity, respectively. Computed tomography is superior to MR in the assessment of tumor resectability, with accuracy rates of up to 86.8% and 78.9%, respectively. Close attention to secondary signs of pancreatic cancer, such as pancreatic duct dilatation, abrupt pancreatic duct caliber change, and parenchymal atrophy, are critical in the diagnosis of pancreatic cancer. Emerging techniques such as radiomics and molecular imaging have the potential of identifying malignant precursors and lead to earlier disease diagnosis. The results of these promising techniques need to be validated in larger clinical studies.
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Measurement and scan reproducibility of parameters of intravoxel incoherent motion in renal tumor and normal renal parenchyma: a preliminary research at 3.0 T MR. Abdom Radiol (NY) 2018; 43:1739-1748. [PMID: 29071436 DOI: 10.1007/s00261-017-1361-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
PURPOSE To prospectively estimate measurement and scan reproducibility of parameters of intravoxel incoherent motion (IVIM) in renal tumors, normal renal cortex, and medulla. METHODS Twenty-four consecutive patients (twelve males and twelve females; median age 56.7 years, range 32-71 years) with 25 renal tumors (20 renal cell carcinomas, one urothelium carcinoma, three angiomyolipomas, and one oncocytoma) were examined twice using IVIM1 and IVIM2 with 9 and 16 b values, respectively, at 3.0 T. All the patients were re-scanned in 24-48 h. Regions of interest (ROIs) were placed in solid part of tumor, normal cortex, and medulla to derive IVIM parameters D (true diffusion coefficient), D* (pseudodiffusion coefficient), and f (perfusion fraction of pseudodiffusion). Differences in parameters between two IVIM sets and intra-observer, inter-observer, and scan-rescan differences were assessed using paired t tests. Intra-observer, inter-observer, and scan-rescan reproducibility were assessed by measuring coefficient of variation and Bland-Altman limits of agreements. RESULTS Intra-observer reproducibility of renal tumors, normal renal cortex, and medulla was excellent for apparent diffusion coefficient (ADC; CV: 3.45%-5.34%, BA-LA: -14% to 18%) and D (CV: 3.65% to 6.04%, BA-LA: -18% to 19%), good for f (CV: 11.96%-16.08%, BA-LA: -76.4% to 92.1% except f of medulla with CV of 32.59% and BA-LA of -76.4% to 92.1% in IVIM1), and poor for D* (CV: 25.0% to 75.4%, BA-LA: -111% to 150%). The same order was in inter-observer reproducibility analysis. Scan-rescan reproducibility was the worst of the three parameters. Renal medulla showed worse reproducibility than renal tumors and the normal cortex. The metrics of IVIM2 had better reproducibility than IVIM1. CONCLUSION Excellent reproducibility evaluation for ADC and D, good for f, and poor for D* derived from IVIM was performed in renal tumors, normal renal cortex, and medulla. D* has limited reliability and scan-rescan reproducibility should be improved.
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Intravoxel Incoherent Motion: Model-Free Determination of Tissue Type in Abdominal Organs Using Machine Learning. Invest Radiol 2018; 52:747-757. [PMID: 28742733 DOI: 10.1097/rli.0000000000000400] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
PURPOSE For diffusion data sets including low and high b-values, the intravoxel incoherent motion model is commonly applied to characterize tissue. The aim of the present study was to show that machine learning allows a model-free approach to determine tissue type without a priori assumptions on the underlying physiology. MATERIALS AND METHODS In 8 healthy volunteers, diffusion data sets were acquired using an echo-planar imaging sequence with 16 b-values in the range between 0 and 1000 s/mm. Using the k-nearest neighbors technique, the machine learning algorithm was trained to distinguish abdominal organs (liver, kidney, spleen, muscle) using the signal intensities at different b-values as training features. For systematic variation of model complexity (number of neighbors), performance was assessed by calculation of the accuracy and the kappa coefficient (κ). Most important b-values for tissue discrimination were determined by principal component analysis. RESULTS The optimal trade-off between model complexity and overfitting was found in the range between K = 11 to 13. On "real-world" data not previously applied to optimize the algorithm, the k-nearest neighbors algorithm was capable to accurately distinguish tissue types with best accuracy of 94.5% and κ = 0.92 reached for intermediate model complexity (K = 11). The principal component analysis showed that most important b-values are (with decreasing importance): b = 1000 s/mm, b = 970 s/mm, b = 750 s/mm, b = 20 s/mm, b = 620 s/mm, and b = 40 s/mm. Applying a reduced set of 6 most important b-values, still a similar accuracy was achieved on the real-world data set with an average accuracy of 93.7% and a κ coefficient of 0.91. CONCLUSIONS Machine learning allows for a model-free determination of tissue type using intra voxel incoherent motion signal decay curves as features. The technique may be useful for segmentation of abdominal organs or distinction between healthy and pathological tissues.
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Zarinabad N, Meeus EM, Manias K, Foster K, Peet A. Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis. JMIR Med Inform 2018; 6:e30. [PMID: 29720361 PMCID: PMC5956158 DOI: 10.2196/medinform.9171] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 01/10/2018] [Accepted: 01/26/2018] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. OBJECTIVE The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. METHODS The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. RESULTS Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. CONCLUSIONS MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments.
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Affiliation(s)
- Niloufar Zarinabad
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Birmingham Children Hospital NHS Trust, Birmingham, United Kingdom
| | - Emma M Meeus
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Birmingham Children Hospital NHS Trust, Birmingham, United Kingdom.,Physical Sciences of Imaging in Biomedical Sciences Doctoral Training Centre, University of Birmingham, Birmingham, United Kingdom
| | - Karen Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Birmingham Children Hospital NHS Trust, Birmingham, United Kingdom
| | - Katharine Foster
- Birmingham Children Hospital NHS Trust, Birmingham, United Kingdom
| | - Andrew Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom.,Birmingham Children Hospital NHS Trust, Birmingham, United Kingdom
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Bali MA, Pullini S, Metens T, Absil J, Chao SL, Marechal R, Matos C, Peerboccus BM, Van Laethem JL. Assessment of response to chemotherapy in pancreatic ductal adenocarcinoma: Comparison between diffusion-weighted MR quantitative parameters and RECIST. Eur J Radiol 2018; 104:49-57. [PMID: 29857866 DOI: 10.1016/j.ejrad.2018.04.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 03/22/2018] [Accepted: 04/24/2018] [Indexed: 02/08/2023]
Abstract
PURPOSE To prospectively assess chemotherapy-induced changes in pancreatic ductal adenocarcinoma (PDA) with diffusion-weighted (DW)-MR quantitative metrics, including apparent diffusion coefficient (ADC) and histogram-derived parameters, compared with RECIST 1.1. METHODS 24 patients underwent DW-MR at baseline, week-2 and week-8 after chemotherapy initiation. Tumour diameter was assessed on T2-weighted images. Regions-of-interest (ROI) were drawn on ADC map for ROI-ADC. Volume segmentation (b = 1000 s/mm2 images) provided DW-volume and histogram-derived diffusion parameters (H-ADC, H-D and H-PF). All variables and their relative change were compared to baseline or between responders and non-responders. Discriminant analysis was performed. RESULTS 15/24 patients were responders. RECIST 1.1 correctly characterized 6/15 responders at week-8. At week-2, in responders DW-volume decreased (P = .002); ROI-ADC mean H-D increased (P = .047; P = .048;). The 25th percentile H-D increased in responders and decreased in non-responders (P = .016; P = .048). At week-8 in responders DW-volume decreased and ROI-ADC mean, 25th, 50th, 75th percentiles of H-ADC and H-D increased (P < .05). No changes were observed in non-responders (P > .05). At week-2, 25th percentile of H-D and H-PF relative change correctly classified 20/24 patients (P = .003); at week-8, DW-volume relative change correctly classified 22/24 patients (P < .0001). CONCLUSIONS ROI-ADC, DW-volume and histogram-derived diffusion parameters are more accurate to categorize responding and non-responding PDA patients treated with chemotherapy compared with RECIST 1.1.
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Affiliation(s)
- Maria Antonietta Bali
- Department of Radiology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Serena Pullini
- Institute of Diagnostic Radiology, University of Udine, Udine, Italy.
| | - Thierry Metens
- Department of Radiology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Julie Absil
- Department of Radiology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Shih-Li Chao
- Department of Radiology, Institute Jules Bordet, Boulevard de Waterloo, 121, 1000 Brussels, Belgium.
| | - Raphael Marechal
- Department of Gastroenterology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Celso Matos
- Department of Radiology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Bibi Mooneera Peerboccus
- Department of Radiology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
| | - Jean-Luc Van Laethem
- Department of Gastroenterology, Erasme Hospital, Université Libre de Bruxelles, Route de Lennik, 808, 1070 Brussels, Belgium.
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Lu B, Yang X, Xiao X, Chen Y, Yan X, Yu S. Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Primary Rectal Carcinoma: Correlation with Histopathology. Med Sci Monit 2018; 24:2429-2436. [PMID: 29679528 PMCID: PMC5930975 DOI: 10.12659/msm.908574] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background Comprehensive and precise assessment of rectal carcinoma is crucial before surgery to plan an individual treatment strategy. New functional techniques, such as intravoxel incoherent motion (IVIM), have emerged and could lead to more detailed information. The aim of this study was to evaluate the difference between the rectal tumor parenchyma and normal wall by IVIM and to explore the correlations of IVIM parameters and histopathology. Material/Methods We prospectively enrolled 128 patients with pathologically proven rectal non-mucinous carcinoma with differentiation degree and 16 patients with mucinous carcinoma. All patients underwent routine MR examination and IVIM sequence. The IVIM maps were automatically generated and 3 ROIs were drawn on the maximal rectal tumor parenchyma and normal rectal wall. The Wilcoxon signed rank test, t test, Mann-Whitney U test, and Spearman’s rank correlation test were performed. Results All IVIM parameters demonstrated the difference between rectal tumor parenchyma and normal wall (PD<0.001; PD*=0.014; Pf<0.001). Poorly differentiated carcinoma had a significantly lower f value (Pf=0.049) than well/moderately-differentiated carcinoma. In addition, mucinous carcinoma had a higher D (PD=0.001) and a lower D* value (PD*=0.001) than non-mucinous carcinoma. Correlation analysis between IVIM parameters and histopathology showed that D (|r|=0.538, PD=0.000) and D* (|r|=0.267, PD*=0.001) had statistically significant correlations with histological type and f (|r|=0.175, Pf=0.048) was significantly correlated with differentiation degree. Conclusions The IVIM parameters of rectal tumor parenchyma and normal wall were significantly different. D appears to be a valid and promising parameter to indicate histological features of rectal carcinoma.
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Affiliation(s)
- Baolan Lu
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China (mainland)
| | - Xinyue Yang
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China (mainland)
| | - Xiaojuan Xiao
- Department of Radiology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China (mainland)
| | - Yan Chen
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China (mainland)
| | - Xu Yan
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, China (mainland)
| | - Shenping Yu
- Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China (mainland)
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Ma W, Zhang G, Ren J, Pan Q, Wen D, Zhong J, Zhang Z, Huan Y. Quantitative parameters of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI): potential application in predicting pathological grades of pancreatic ductal adenocarcinoma. Quant Imaging Med Surg 2018; 8:301-310. [PMID: 29774183 DOI: 10.21037/qims.2018.04.08] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background The aim of this study was to compare intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) parameters such as standard apparent diffusion coefficient (ADCstandard), pure diffusion coefficient (Dslow), pseudodiffusion coefficient (Dfast) and perfusion fraction (ƒ) for differentiating pancreatic ductal adenocarcinoma (PDAC) with different pathological grades. Methods Institutional Review Board of our hospital approved this study protocol. Subjects comprised 38 PDACs confirmed by pathology. Pancreatic multiple b values DWI with 15 b values of 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1200, 1,500, and 2,000 s/mm2 was performed using GE Discovery MR750 3.0T scanner. ADCstandard, Dslow, Dfast and ƒ values of all PDACs were calculated using mono- and bi-exponential models. Parameters of well/moderately differentiated and poorly differentiated PDAC were compared using Independent Sample t-test. P values <0.05 were considered significant. Results Mean Dslow value of well/moderately differentiated PDAC was significantly lower than that of poorly differentiated PDAC (0.540×10-3vs. 0.676×10-3 mm2/s, P<0.001). Mean ƒ value of well/moderately differentiated PDAC was significantly higher than that of poorly differentiated PDAC (60.3% vs. 38.4%, P<0.001). The area under curve value of ƒ in differentiating well/moderately differentiated PDAC from poorly differentiated PDAC was slightly higher than that of Dslow (0.894>0.865). When the Dslow value was less than or equal to 0.599×10-3 mm2/s, the sensitivity and specificity were 100% and 84.6% respectively. When ƒ value was greater than 49.6%, the sensitivity and specificity were 92.0% and 84.6% respectively. Conclusions Dslow and ƒ derived from IVIM-DWI model can be used to distinguish well/moderately differentiated PDAC from poorly differentiated PDAC. And to serve this purpose, Dslow and ƒ have high diagnostic performance. IVIM-DWI is a promising and non-invasive tool for predicting pathological grade of PDAC.
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Affiliation(s)
- Wanling Ma
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Guangwen Zhang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Jing Ren
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Qi Pan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Didi Wen
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Jinman Zhong
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
| | - Zhuoli Zhang
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Yi Huan
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China
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Luo M, Zhang L, Jiang XH, Zhang WD. Intravoxel incoherent motion: application in differentiation of hepatocellular carcinoma and focal nodular hyperplasia. Diagn Interv Radiol 2018; 23:263-271. [PMID: 28703102 DOI: 10.5152/dir.2017.16595] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE We aimed to explore whether intravoxel incoherent motion (IVIM)-related parameters of hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH) demonstrate differences that could be used to differentiate and improve diagnostic efficiency. METHODS A total of 27 patients, including 22 with HCC and 5 with FNH, underwent liver 3.0 T magnetic resonance imaging for routine sequences. They were concurrently examined by IVIM diffusion-weighted imaging (DWI) scanning with 11 different b values (0-800 s/mm2). IVIM-derived parameters, such as pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADCtotal), were quantified automatically by post-processing software and compared between HCC and FNH groups. A receiver operating characteristic (ROC) curve was then created to predict their diagnostic value. RESULTS D* was weak in terms of reproducibility among the other parameters. ADCtotal, D, and D* were significantly lower in the HCC group than in the FNH group, while f did not show a significant difference. ADCtotal and D had the largest area under the curve values (AUC; 0.915 and 0.897, respectively) and similarly high efficacy to differentiate the two conditions. CONCLUSION IVIM provides a new modality to differentiate the HCC and FNH. ADCtotal and D demonstrated outstanding and comparable diagnosing utility.
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Affiliation(s)
- Ma Luo
- Department of Radiology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, China.
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Zhang Y, Zhu X, Liu R, Wang X, Sun G, Song J, Lu J, Zhang H. Combination of Pre-Treatment DWI-Signal Intensity and S-1 Treatment: A Predictor of Survival in Patients with Locally Advanced Pancreatic Cancer Receiving Stereotactic Body Radiation Therapy and Sequential S-1. Transl Oncol 2018; 11:399-405. [PMID: 29455086 PMCID: PMC5852410 DOI: 10.1016/j.tranon.2018.01.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Revised: 01/03/2018] [Accepted: 01/16/2018] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVE: To identify whether the combination of pre-treatment radiological and clinical factors can predict the overall survival (OS) in patients with locally advanced pancreatic cancer (LAPC) treated with stereotactic body radiation and sequential S-1 (a prodrug of 5-FU combined with two modulators) therapy with improved accuracy compared with that of established clinical and radiologic risk models. METHODS: Patients admitted with LAPC underwent diffusion weighted imaging (DWI) scan at 3.0-T (b = 600 s/mm2). The mean signal intensity (SIb = 600) of region-of-interest (ROI) was measured. The Log-rank test was done for tumor location, biliary stent, S-1, and other treatments and the Cox regression analysis was done to identify independent prognostic factors for OS. Prediction error curves (PEC) were used to assess potential errors in prediction of survival. The accuracy of prediction was evaluated by Integrated Brier Score (IBS) and C index. RESULTS: 41 patients were included in this study. The median OS was 11.7 months (2.8-23.23 months). The 1-year OS was 46%. Multivariate analysis showed that pre-treatment SIb = 600 value and administration of S-1 were independent predictors for OS. The performance of pre-treatment SIb = 600 and S-1 treatment in combination was better than that of SIb = 600 or S-1 treatment alone. CONCLUSION: The combination of pre-treatment SIb = 600 and S-1 treatment could predict the OS in patients with LAPC undergoing SBRT and sequential S-1 therapy with improved accuracy compared with that of established clinical and radiologic risk models.
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Affiliation(s)
- Yu Zhang
- Department of radiology, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China.
| | - Xiaofei Zhu
- Department of oncology radiation, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China
| | - Ri Liu
- Department of radiology, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China
| | - Xianglian Wang
- Health Management Department of Nanfang hospital, 510515, P.R. China
| | - Gaofeng Sun
- Department of Nuclear Medicine, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China
| | - Jiaqi Song
- Department of health statistics, Second Military Medical University, Xiangyin Road 800, Yangpu district, Shanghai, 200433, P.R. China
| | - Jianping Lu
- Department of radiology, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China
| | - Huojun Zhang
- Department of oncology radiation, Changhai Hospital Affiliated to the Second Military Medical University, Changhai Road 168, Yangpu district, Shanghai, 200433, P.R. China.
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Mayer P, Dinkic C, Jesenofsky R, Klauss M, Schirmacher P, Dapunt U, Hackert T, Uhle F, Hänsch GM, Gaida MM. Changes in the microarchitecture of the pancreatic cancer stroma are linked to neutrophil-dependent reprogramming of stellate cells and reflected by diffusion-weighted magnetic resonance imaging. Theranostics 2018; 8:13-30. [PMID: 29290790 PMCID: PMC5743457 DOI: 10.7150/thno.21089] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 09/13/2017] [Indexed: 01/06/2023] Open
Abstract
In pancreatic cancer (PDAC) intratumor infiltration of polymorphonuclear neutrophils (PMN) is associated with histologically apparent alterations of the tumor growth pattern. The aim of this study was to examine possible associations between PMN infiltration, tumor microarchitecture, and water diffusivity in diffusion-weighted magnetic resonance imaging (DW-MRI), and to further asses the underlying mechanisms. Methods: DW-MRI was performed in 33 PDAC patients prior to surgery. In parallel, tissue specimen were examined histologically for growth pattern, azurocidin-positive PMN infiltrates, and the presence of alpha-smooth muscle actin (α-SMA) and metalloproteinase 9 (MMP9)-positive myofibroblastic cells. For confirmation of the histological findings, a tissue microarray of a second cohort of patients (n=109) was prepared and examined similarly. For in vitro studies, the pancreatic stellate cell line RLT was co-cultivated either with isolated PMN, PMN-lysates, or recombinant azurocidin and characterized by Western blot, flow cytometry, and proteome profiler arrays. Results: Tumors with high PMN density showed restricted water diffusion in DW-MRI and histologic apparent alterations of the tumor microarchitecture (microglandular, micropapillary, or overall poorly differentiated growth pattern) as opposed to tumors with scattered PMN. Areas with altered growth pattern lacked α-SMA-positive myofibroblastic cells. Tissue microarrays confirmed a close association of high PMN density with alterations of the tumor microarchitecture and revealed a significant association of high PMN density with poor histologic grade of differentiation (G3). In vitro experiments provided evidence for direct effects of PMN on stellate cells, where a change to a spindle shaped cell morphology in response to PMN and to PMN-derived azurocidin was seen. Azurocidin incorporated into stellate cells, where it associated with F-actin. Down-regulation of α-SMA was seen within hours, as was activation of the p38-cofilin axis, up-regulation of MMP9, and acquisition of intracellular lipid droplets, which together indicate a phenotype switch of the stellate cells. Conclusion: In PDAC, PMN infiltrates are associated with alterations of the tumor microarchitecture. As a causal relationship, we propose a reprogramming of stellate cells by PMN-derived azurocidin towards a phenotype, which affects the microarchitecture of the tumor.
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Park H, Jang K, Song K, Kim S, Kim Y, Cha M, Choi SY, Min K. Value of unenhanced MRI with diffusion-weighted imaging for detection of primary small (≤20 mm) solid pancreatic tumours and prediction of pancreatic ductal adenocarcinoma. Clin Radiol 2017; 72:1076-1084. [DOI: 10.1016/j.crad.2017.07.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 06/27/2017] [Accepted: 07/12/2017] [Indexed: 02/07/2023]
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Meeus EM, Zarinabad N, Manias KA, Novak J, Rose HEL, Dehghani H, Foster K, Morland B, Peet AC. Diffusion-weighted MRI and intravoxel incoherent motion model for diagnosis of pediatric solid abdominal tumors. J Magn Reson Imaging 2017; 47:1475-1486. [PMID: 29159937 PMCID: PMC6001424 DOI: 10.1002/jmri.25901] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/06/2017] [Indexed: 12/24/2022] Open
Abstract
Background Pediatric retroperitoneal tumors in the renal bed are often large and heterogeneous, and their diagnosis based on conventional imaging alone is not possible. More advanced imaging methods, such as diffusion‐weighted (DW) MRI and the use of intravoxel incoherent motion (IVIM), have the potential to provide additional biomarkers that could facilitate their noninvasive diagnosis. Purpose To assess the use of an IVIM model for diagnosis of childhood malignant abdominal tumors and discrimination of benign from malignant lesions. Study Type Retrospective. Population Forty‐two pediatric patients with abdominal lesions (n = 32 malignant, n = 10 benign), verified by histopathology. Field Strength/Sequence 1.5T MRI system and a DW‐MRI sequence with six b‐values (0, 50, 100, 150, 600, 1000 s/mm2). Assessment Parameter maps of apparent diffusion coefficient (ADC), and IVIM maps of slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were computed using a segmented fitting model. Histograms were constructed for whole‐tumor regions of each parameter. Statistical Tests Comparison of histogram parameters of and their diagnostic performance was determined using Kruskal–Wallis, Mann–Whitney U, and receiver‐operating characteristic (ROC) analysis. Results IVIM parameters D* and f were significantly higher in neuroblastoma compared to Wilms' tumors (P < 0.05). The ROC analysis showed that the best diagnostic performance was achieved with D* 90th percentile (area under the curve [AUC] = 0.935; P = 0.002; cutoff value = 32,376 × 10−6 mm2/s) and f mean values (AUC = 1.00; P < 0.001; cutoff value = 14.7) in discriminating between neuroblastoma (n = 11) and Wilms' tumors (n = 8). Discrimination between tumor types was not possible with IVIM D or ADC parameters. Malignant tumors revealed significantly lower ADC, D, and higher D* values than in benign lesions (all P < 0.05). Data Conclusion IVIM perfusion parameters could distinguish between malignant childhood tumor types, providing potential imaging biomarkers for their diagnosis. Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1475–1486.
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Affiliation(s)
- Emma M Meeus
- Physical Sciences of Imaging in Biomedical Sciences (PSIBS) Doctoral Training Centre, University of Birmingham, UK.,Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Niloufar Zarinabad
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Karen A Manias
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Jan Novak
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Heather E L Rose
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Hamid Dehghani
- Physical Sciences of Imaging in Biomedical Sciences (PSIBS) Doctoral Training Centre, University of Birmingham, UK.,School of Computer Science, University of Birmingham, UK
| | - Katharine Foster
- Department of Radiology, Birmingham Children's Hospital, Birmingham, UK
| | - Bruce Morland
- Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, UK.,Department of Oncology, Birmingham Children's Hospital, Birmingham, UK
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Meeus EM, Novak J, Dehghani H, Peet AC. Rapid measurement of intravoxel incoherent motion (IVIM) derived perfusion fraction for clinical magnetic resonance imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 31:269-283. [PMID: 29075909 PMCID: PMC5871652 DOI: 10.1007/s10334-017-0656-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2017] [Revised: 09/26/2017] [Accepted: 09/27/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVE This study aimed to investigate the reliability of intravoxel incoherent motion (IVIM) model derived parameters D and f and their dependence on b value distributions with a rapid three b value acquisition protocol. MATERIALS AND METHODS Diffusion models for brain, kidney, and liver were assessed for bias, error, and reproducibility for the estimated IVIM parameters using b values 0 and 1000, and a b value between 200 and 900, at signal-to-noise ratios (SNR) 40, 55, and 80. Relative errors were used to estimate optimal b value distributions for each tissue scenario. Sixteen volunteers underwent brain DW-MRI, for which bias and coefficient of variation were determined in the grey matter. RESULTS Bias had a large influence in the estimation of D and f for the low-perfused brain model, particularly at lower b values, with the same trends being confirmed by in vivo imaging. Significant differences were demonstrated in vivo for estimation of D (P = 0.029) and f (P < 0.001) with [300,1000] and [500,1000] distributions. The effect of bias was considerably lower for the high-perfused models. The optimal b value distributions were estimated to be brain500,1000, kidney300,1000, and liver200,1000. CONCLUSION IVIM parameters can be estimated using a rapid DW-MRI protocol, where the optimal b value distribution depends on tissue characteristics and compromise between bias and variability.
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Affiliation(s)
- Emma M Meeus
- Physical Sciences of Imaging in Biomedical Sciences (PSIBS) Doctoral Training Centre, University of Birmingham, Birmingham, B15 2TT, UK.,Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK.,Department of Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Jan Novak
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK.,Department of Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Hamid Dehghani
- Physical Sciences of Imaging in Biomedical Sciences (PSIBS) Doctoral Training Centre, University of Birmingham, Birmingham, B15 2TT, UK.,School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Andrew C Peet
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK. .,Department of Oncology, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, B4 6NH, UK.
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Ma C, Li J, Boukar MB, Yang P, Wang L, Chen L, Su L, Qu J, Chen SY, Hao Q, Lu JP. Optimized ROI size on ADC measurements of normal pancreas, pancreatic cancer and mass-forming chronic pancreatitis. Oncotarget 2017; 8:99085-99092. [PMID: 29228754 PMCID: PMC5716794 DOI: 10.18632/oncotarget.18457] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Accepted: 05/23/2017] [Indexed: 12/20/2022] Open
Abstract
Objectives To investigate the effects of region of interest (ROI) sizes on apparent diffusion coefficient (ADC) measurements for the differentiation of normal pancreas (NP), pancreatic ductal adenocarcinoma (PDAC) and mass-forming chronic pancreatitis (MFCP). Results There were no significant differences for the mean ADCs measured by 12 different-size ROIs for MFCP, or PDAC and NP (P = 0.858–1.0). With the increase of ROI size (≥ 55 mm2), ADCs of PDAC were significantly lower than those of NP (all P < 0.05), but there was no difference of the accuracy in ADC for differentiating the two groups only at a ROI size of 214 mm2. When ROI size was above 99 mm2, ADCs of MFCP were significantly lower than those of NP (all P < 0.05). There were no significant differences for any of the mean ADCs measured by 12 different-size ROIs between PDAC and MFCP (P > 0.05). Materials and Methods Diffusion-weighted imaging (DWI) was performed on 89 participants: 64 with PDAC, 7 with MFCP, as well as 18 healthy volunteers. ADC maps were created using mono-exponential model. A homemade software was used to measure the mean ADC values of 12 concentric round ROIs (areas: 15, 46, 55, 82, 99, 121, 134, 152, 161, 189, 214, 223, and 245 mm2) for the mass of lesions and the NP tissue. Conclusions In ADC measurements, the optimized ROI size is 214 mm2 for the differentiation of PDAC and NP; ROI size of ≥ 99 mm2 is recommended to differentiate between MFCP and NP. ADC was not useful for the differentiation of PDAC and MFCP.
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Affiliation(s)
- Chao Ma
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Jing Li
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Mbaiaoure Barak Boukar
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Panpan Yang
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Li Wang
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Luguang Chen
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Li Su
- School of Pharmacy, Second Military Medical University, Shanghai, China
| | - Jianxun Qu
- GE Healthcare, MR Group, Shanghai, China
| | - Shi-Yue Chen
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Qiang Hao
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
| | - Jian-Ping Lu
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, Shanghai, China
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Ma C, Li Y, Wang L, Wang Y, Zhang Y, Wang H, Chen S, Lu J. Intravoxel incoherent motion DWI of the pancreatic adenocarcinomas: monoexponential and biexponential apparent diffusion parameters and histopathological correlations. Cancer Imaging 2017; 17:12. [PMID: 28454564 PMCID: PMC5410078 DOI: 10.1186/s40644-017-0114-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 04/19/2017] [Indexed: 02/06/2023] Open
Abstract
Background To investigate the associations between the diffusion parameters obtained from multiple-b-values diffusion weighted imaging (DWI) of pancreatic ductal adenocarcinoma (PDAC) and the aggressiveness and local stage prediction, and assess the values of the quantitative parameters for the discrimination of tumors from healthy pancreas. Methods Fifty-one patients with surgical pathology-proven PDAC (size, 35 ± 12 mm) and fifty-seven healthy volunteers were enrolled. Diffusion parameters including monoexponential apparent diffusion coefficient (ADCb and ADCtotal) and biexponential intravoxel incoherent motion (IVIM) parameters (ADCslow, ADCfast and f) based on 9 b-values (0 to 1000s/mm2) DWI were calculated for the lesions and the healthy pancreas. These parameters were compared by grades of differentiation, lymph node status, tumor stage and location. The diagnostic performances were calculated and compared by using the receiver operating characteristic curves (ROC) analyses. Results There was no statistically significant difference in ADCb, ADCtotal, ADCslow, ADCfast or f between PDAC stage T1/T2 and stage T3/T4 or moderately differentiated versus poorly differentiated PDAC (p = 0.060-0.941). In addition, no significant differences were observed for the quantitative parameters between tumors located in the pancreatic head versus other pancreatic regions (p = 0.203-0.954) or between tumors with and without metastatic peri-pancreatic lymph nodes (p = 0.313-0.917). ADC25-600, ADC1000, ADCtotal and ADCfast were significantly lower for PDAC compared the healthy pancreas (all p < 0.05). ROC analyses showed the area under curve for ADC20 was the largest (0.911) to distinguish PDAC from normal pancreas (cut-off value, 5.58 × 10−3mm2/s) and had the highest combined sensitivity (89.5%) and specificity (82.4%). Conclusions Multiple-b-values DWI derived monoexponential and biexponential parameters of PDAC do not exhibit significance dependence on tumor grade or tumor characteristics. ADC20 provided the best accuracy for differentiating PDAC from healthy pancreas in the study.
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Affiliation(s)
- Chao Ma
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Yanjun Li
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Li Wang
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Yang Wang
- Department of Pathology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, China
| | - Yong Zhang
- MR Group, GE Healthcare, No. 1 Huatuo Road, Shanghai, China
| | - He Wang
- MR Group, GE Healthcare, No. 1 Huatuo Road, Shanghai, China
| | - Shiyue Chen
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China
| | - Jianping Lu
- Department of Radiology, Changhai Hospital of Shanghai, The Second Military Medical University, No.168 Changhai Road, Shanghai, 200433, China.
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Best LMJ, Rawji V, Pereira SP, Davidson BR, Gurusamy KS. Imaging modalities for characterising focal pancreatic lesions. Cochrane Database Syst Rev 2017; 4:CD010213. [PMID: 28415140 PMCID: PMC6478242 DOI: 10.1002/14651858.cd010213.pub2] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions. OBJECTIVES To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions. SEARCH METHODS We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively. SELECTION CRITERIA We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively. DATA COLLECTION AND ANALYSIS Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data. MAIN RESULTS We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing. AUTHORS' CONCLUSIONS We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.
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Affiliation(s)
- Lawrence MJ Best
- Royal Free Campus, UCL Medical SchoolDepartment of SurgeryRowland Hill StreetLondonUKNW32PF
| | - Vishal Rawji
- University College London Medical SchoolLondonUK
| | - Stephen P Pereira
- Royal Free Hospital CampusUCL Institute for Liver and Digestive HealthUpper 3rd FloorLondonUKNW3 2PF
| | - Brian R Davidson
- Royal Free Campus, UCL Medical SchoolDepartment of SurgeryRowland Hill StreetLondonUKNW32PF
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Gurney-Champion OJ, Bruins Slot T, Lens E, van der Horst A, Klaassen R, van Laarhoven HWM, van Tienhoven G, van Hooft JE, Nederveen AJ, Bel A. Quantitative assessment of biliary stent artifacts on MR images: Potential implications for target delineation in radiotherapy. Med Phys 2017; 43:5603. [PMID: 27782717 DOI: 10.1118/1.4962476] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
PURPOSE Biliary stents may cause susceptibility artifacts, gradient-induced artifacts, and radio frequency (RF) induced artifacts on magnetic resonance images, which can hinder accurate target volume delineation in radiotherapy. In this study, the authors investigated and quantified the magnitude of these artifacts for stents of different materials. METHODS Eight biliary stents made of nitinol, platinum-cored nitinol, stainless steel, or polyethylene from seven vendors, with different lengths (57-98 mm) and diameters (3.0-11.7 mm), were placed in a phantom. To quantify the susceptibility artifacts sequence-independently, ΔB0-maps and T2∗-maps were acquired at 1.5 and 3 T. To study the effect of the gradient-induced artifacts at 3 T, signal decay in images obtained with maximum readout gradient-induced artifacts was compared to signal decay in reference scans. To quantify the RF induced artifacts at 3 T, B1-maps were acquired. Finally, ΔB0-maps and T2∗-maps were acquired at 3 T of two pancreatic cancer patients who had received platinum-cored nitinol biliary stents. RESULTS Outside the stent, susceptibility artifacts dominated the other artifacts. The stainless steel stent produced the largest susceptibility artifacts. The other stents caused decreased T2∗ up to 5.1 mm (1.5 T) and 8.5 mm (3 T) from the edge of the stent. For sequences with a higher bandwidth per voxel (1.5 T: BWvox > 275 Hz/voxel; 3 T: BWvox > 500 Hz/voxel), the B0-related susceptibility artifacts were negligible (<0.2 voxels). The polyethylene stent showed no artifacts. In vivo, the changes in B0 and T2∗ induced by the stent were larger than typical variations in B0 and T2∗ induced by anatomy when the stent was at an angle of 30° with the main magnetic field. CONCLUSIONS Susceptibility artifacts were dominating over the other artifacts. The magnitudes of the susceptibility artifacts were determined sequence-independently. This method allows to include additional safety margins that ensure target irradiation.
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Affiliation(s)
- Oliver J Gurney-Champion
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands and Department of Radiology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Thijs Bruins Slot
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Eelco Lens
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Astrid van der Horst
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Remy Klaassen
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands and Laboratory for Experimental Oncology and Radiobiology, Center for Experimental Molecular Medicine, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Hanneke W M van Laarhoven
- Department of Medical Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Geertjan van Tienhoven
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Jeanin E van Hooft
- Department of Gastroenterology and Hepatology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
| | - Arjan Bel
- Department of Radiation Oncology, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam 1105 AZ, The Netherlands
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Deng Y, Li X, Lei Y, Liang C, Liu Z. Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. Acta Radiol 2016; 57:1310-1317. [PMID: 25972370 DOI: 10.1177/0284185115586091] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Background Using imaging techniques to diagnose malignant and inflammatory lesions in the lung can be challenging. Purpose To compare intravoxel incoherent motion (IVIM) and apparent diffusion coefficient (ADC) magnetic resonance imaging (MRI) analysis in their ability to discriminate lung cancer from focal inflammatory lung lesions. Material and Methods Thirty-eight patients with lung masses were included: 30 lung cancers and eight inflammatory lesions. Patients were imaged with 3.0T MRI diffusion weighted imaging (DWI) using 10 b values (range, 0-1000 s/mm2). Tissue diffusivity ( D), pseudo-diffusion coefficient ( D*), and perfusion fraction ( f) were calculated using segmented biexponential analysis. ADC (total) was calculated with monoexponential fitting of the DWI data. D, D*, f, and ADC were compared between lung cancer and inflammatory lung lesions. Receiver operating characteristic analysis was performed for all DWI parameters. Results The ADC was significantly higher for inflammatory lesions than for lung cancer ([1.21 ± 0.20] × 10-3 mm2/s vs. [0.97 ± 0.15] × 10-3 mm2/s; P = 0.004). By IVIM, f was found to be significantly higher in inflammatory lesions than lung cancer ([46.10 ± 12.92] % vs. [29.29 ± 10.89] %; P = 0.005). There was no difference in D and D* between lung cancer and inflammatory lesions ( P = 0.747 and 0.124, respectively). f showed comparable diagnostic performance with ADC in differentiating lung cancer from inflammatory lung lesions, with areas under the curve of 0.833 and 0.826, sensitivity 80.0% and 73.3%, and specificity 75.0% and 87.5%, respectively. Conclusion The IVIM parameter f value provides comparable diagnostic performance with ADC and could be used as a surrogate marker for differentiating lung cancer from inflammatory lesions.
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Affiliation(s)
- Yu Deng
- Southern Medical University, Guangzhou, PR China
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, PR China
- Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China
| | - Xinchun Li
- Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China
| | - Yongxia Lei
- Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, PR China
| | - Changhong Liang
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, PR China
| | - Zaiyi Liu
- Department of Radiology, Guangdong Academy of Medical Sciences, Guangdong General Hospital, Guangzhou, PR China
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A Standardized Parameter-Free Algorithm for Combined Intravoxel Incoherent Motion and Diffusion Kurtosis Analysis of Diffusion Imaging Data. Invest Radiol 2016; 51:203-10. [PMID: 26561050 DOI: 10.1097/rli.0000000000000223] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
OBJECTIVES The aims of this study were to implement and systematically evaluate the performance of a new parameter-free segmented algorithm for analysis of diffusion imaging data using a combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) model of spin diffusion in comparison with the simpler intravoxel incoherent motion (IVIM) model. MATERIALS AND METHODS A multistep algorithm was implemented intended to separate diffusion kurtosis from IVIM effects in multi-b-value diffusion measurements using an adaptive b-value threshold technique. For each possible b-value threshold (separating diffusion and perfusion effects), diffusion kurtosis analysis of high b-values is followed by IVIM analysis keeping kurtosis parameters fixed. The b-value threshold with smallest Akaike information criterion is chosen as best model solution. The algorithm was tested in diffusion data sets of the upper abdomen from 8 healthy volunteers with 16 different b-values and compared with a standard multistep IVIM analysis. RESULTS The proposed algorithm could successfully be applied to all data sets and provided a significantly better fit of the observed signal decay in all assessed organs (all P < 0.03). Using the proposed IVIM-DKI model of diffusion instead of an IVIM model had a systematic impact on the resulting IVIM parameters: The pure diffusion coefficient and the pseudodiffusion coefficient were significantly increased (P < 0.03 in all assessed organs), accompanied by a decrease in the perfusion fraction in liver, pancreas, renal cortex, and skeletal muscle (all P < 0.02). Optimal b-value thresholds separating diffusion from perfusion effects had a tendency to lower values when the IVIM-DKI model was used. CONCLUSIONS The proposed algorithm provides a new approach for separation of IVIM and kurtosis effects of diffusion data without organ-specific adaptation.
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Hafezi-Nejad N, Singh VK, Johnson SI, Makary MA, Hirose K, Fishman EK, Zaheer A. Surgical approaches to chronic pancreatitis: indications and imaging findings. Abdom Radiol (NY) 2016; 41:1980-96. [PMID: 27207476 DOI: 10.1007/s00261-016-0775-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Chronic pancreatitis (CP) is an irreversible, inflammatory process characterized by progressive fibrosis of the pancreas that can result in abdominal pain, exocrine insufficiency, and diabetes. Inadequate pain relief using medical and/or endoscopic therapies is an indication for surgery. The surgical management of CP is centered around three main operations including pancreaticoduodenectomy (PD), duodenum-preserving pancreatic head resection (DPPHR) and drainage procedures, and total pancreatectomy with islet autotransplantation (TPIAT). PD is the method of choice when there is a high suspicion for malignancy. Combined drainage and resection procedures are associated with pain relief, higher quality of life, and superior short-term and long-term survival in comparison with the PD. TPIAT is a reemerging treatment that may be promising in subjects with intractable pain and impaired quality of life. Imaging examinations have an extensive role in pre-operative and post-operative evaluation of CP patients. Pre-operative advanced imaging examinations including CT and MRI can detect hallmarks of CP such as calcifications, pancreatic duct dilatation, chronic pseudocysts, focal pancreatic enlargement, and biliary ductal dilatation. Post-operative findings may include periportal hepatic edema, pneumobilia, perivascular cuffing and mild pancreatic duct dilation. Imaging can also be useful in the detection of post-operative complications including obstructions, anastomotic leaks, and vascular lesions. Imaging helps identify unique post-operative findings associated with TPIAT and may aid in predicting viability and function of the transplanted islet cells. In this review, we explore surgical indications as well as pre-operative and post-operative imaging findings associated with surgical options that are typically performed for CP patients.
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Intravoxel Incoherent Motion Protocol Evaluation and Data Quality in Normal and Malignant Liver Tissue and Comparison to the Literature. Invest Radiol 2016; 51:90-9. [PMID: 26405835 DOI: 10.1097/rli.0000000000000207] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
OBJECTIVES Although intravoxel incoherent motion (IVIM) becomes more and more popular, there is currently no clear consensus on the number and distribution of b-values to use. In this work, we (1) tested and evaluated the data quality of a 25-b-value IVIM protocol in patients with malignant liver lesions and normal liver tissue as a standard of reference, (2) calculated an optimal b-value distribution and compared with the standard of reference, and (3) compared the 25-b-value protocol with other proposed protocols in the literature. MATERIALS AND METHODS Intravoxel incoherent motion imaging with 25 b-values was performed at 3 T in a total of 15 patients with malignant liver lesions. Reference IVIM parameter maps were calculated in tumor and normal liver tissue. With these parameters, optimal IVIM protocols with reduced numbers of b-values were calculated. These optimal IVIM protocols were again applied to calculate new IVIM parameter maps that were compared with the reference parameter maps by calculating mean relative errors. In addition, 35 other IVIM protocols, as found in literature, were compared in a similar way with the 25-b-value protocol serving as a standard of reference. RESULTS The mean relative error depends on the number of b-values and their distribution. In tumor tissue, the error is higher and more variable than in normal-appearing liver tissue. The largest errors occur in tumor tissue and in the protocols having low numbers of b-values in the IVIM protocols. In the calculated optimal IVIM protocols, the mean relative errors decreased by 40% or more when the number of b-values included increased from 4 to 16. The mean relative errors in the protocols adapted from the literature vary substantially between the various b-value distributions. One optimized 16-b-value protocol, which was found in literature, reduced the average relative error by 80% when compared with 4- and 5-b-value protocols listed in literature. CONCLUSIONS Including more b-values and applying an optimized b-value distribution significantly reduces errors in the IVIM parameter estimates, thereby increasing its accuracy.This effect is even more pronounced in inhomogeneous tumor compared with that in normal liver tissue. However, when restrictions in acquisition time or patient-related factors apply, a minimum of 16 b-values should be considered for reliable results.
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Kim M, Jang KM, Kim JH, Jeong WK, Kim SH, Kang TW, Kim YK, Cha DI, Kim K. Differentiation of mass-forming focal pancreatitis from pancreatic ductal adenocarcinoma: value of characterizing dynamic enhancement patterns on contrast-enhanced MR images by adding signal intensity color mapping. Eur Radiol 2016; 27:1722-1732. [PMID: 27510628 DOI: 10.1007/s00330-016-4522-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2016] [Revised: 07/18/2016] [Accepted: 07/20/2016] [Indexed: 12/17/2022]
Abstract
OBJECTIVES To evaluate the value of dynamic enhancement patterns on contrast-enhanced MR images by adding signal intensity colour mapping (SICM) to differentiate mass-forming focal pancreatitis (MFFP) from pancreatic ductal adenocarcinoma (PDAC). METHODS Forty-one clinicopathologically proven MFFPs and 144 surgically confirmed PDACs were enrolled. Laboratory and MR imaging parameters were used to differentiate MFFP from PDAC. In particular, enhancement patterns on MR images adding SICM were evaluated. By using classification tree analysis (CTA), we determined the predictors for the differentiation of MFFP from PDAC. RESULTS In the CTA, with all parameters except enhancement pattern on SICM images, ductal obstruction grade and T1 hypointensity grade of the pancreatic lesion were the first and second splitting predictor for differentiation of MFFP from PDAC, in order. By adding an enhancement pattern on the SICM images to CTA, the enhancement pattern was the only splitting predictor to differentiate MFFP from PDAC. The CTA model including enhancement pattern on SICM images has sensitivity of 78.0 %, specificity of 99.3 %, and accuracy of 94.6 % for differentiating MFFP from PDAC. CONCLUSION The characterization of enhancement pattern for pancreatic lesions on contrast-enhanced MR images adding SICM would be helpful to differentiate MFFP from PDAC. KEY POINTS • SICM was useful to characterize enhancement pattern. • Enhancement pattern on SICM was the only splitting predictor on CTA. • This model may be useful for differentiating MFFP from PDAC.
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Affiliation(s)
- Mimi Kim
- Department of Radiology, Hanyang Medical Center, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Kyung Mi Jang
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. .,Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Irwon-Dong, Gangnam-gu, Seoul, 135-710, Korea.
| | - Jae-Hun Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Woo Kyoung Jeong
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Seong Hyun Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Tae Wook Kang
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Young Kon Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Dong Ik Cha
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyunga Kim
- Biostatics and Clinical Epidemiology Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea
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Perfusion Assessment Using Intravoxel Incoherent Motion-Based Analysis of Diffusion-Weighted Magnetic Resonance Imaging. Invest Radiol 2016; 51:520-8. [DOI: 10.1097/rli.0000000000000262] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Wegner CS, Gaustad JV, Andersen LMK, Simonsen TG, Rofstad EK. Diffusion-weighted and dynamic contrast-enhanced MRI of pancreatic adenocarcinoma xenografts: associations with tumor differentiation and collagen content. J Transl Med 2016; 14:161. [PMID: 27268062 PMCID: PMC4897888 DOI: 10.1186/s12967-016-0920-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Accepted: 05/20/2016] [Indexed: 01/22/2023] Open
Abstract
PURPOSE The aggressiveness of pancreatic ductal adenocarcinoma (PDAC) is highly dependent on the level of differentiation and the composition of the stroma. In this preclinical study, we investigated the potential of diffusion-weighted magnetic resonance imaging (DW-MRI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as noninvasive methods for providing information on the differentiation and the stroma of PDACs. METHODS Xenografted tumors initiated from four PDAC cell lines (BxPC-3, Capan-2, MIAPaCa-2, and Panc-1) were included in the study. DW-MRI and DCE-MRI were carried out on a 7.05-T MR scanner, and tumor images of ADC (the apparent diffusion coefficient), K (trans) (the volume transfer constant of Gd-DOTA), and v e (the fractional distribution volume of Gd-DOTA) were produced. The level of differentiation and the amount and structure of collagen I and collagen IV were determined by examining histological preparations. RESULTS Differentiated tumors showed lower levels of collagen I and collagen IV than non-differentiated tumors. Significant correlations were found between ADC and v e, and both parameters differentiated clearly between collagen-rich non-differentiated tumors and differentiated tumors containing less collagen. CONCLUSION Differentiated PDAC xenografts show higher ADC values and higher v e values than their non-differentiated counterparts. This observation supports the application of parametric MR images as tumor biomarkers in PDAC. Patients showing low values of ADC and v e most likely have non-differentiated tumors with extensive stroma and, hence, poor prognosis.
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Affiliation(s)
- Catherine S. Wegner
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Jon-Vidar Gaustad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Lise Mari K. Andersen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Trude G. Simonsen
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
| | - Einar K. Rofstad
- Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Norwegian Radium Hospital, Oslo University Hospital, Box 4953, Nydalen, 0424 Oslo, Norway
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