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Liu X, Meng N, Zhou Y, Fu F, Yuan J, Wang Z, Yang Y, Xiong Z, Zou C, Wang M. Tri-Compartmental Restriction Spectrum Imaging Based on 18F-FDG PET/MR for Identification of Primary Benign and Malignant Lung Lesions. J Magn Reson Imaging 2025; 61:830-840. [PMID: 38886922 DOI: 10.1002/jmri.29438] [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: 01/30/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Restriction spectrum imaging (RSI), as an advanced quantitative diffusion-weighted magnetic resonance imaging technique, has the potential to distinguish primary benign and malignant lung lesions. OBJECTIVE To explore how well the tri-compartmental RSI performs in distinguishing primary benign from malignant lung lesions compared with diffusion-weighted imaging (DWI), and to further explore whether positron emission tomography/magnetic resonance imaging (PET/MRI) can improve diagnostic efficacy. STUDY TYPE Prospective. POPULATION 137 patients, including 108 malignant and 29 benign lesions (85 males, 52 females; average age = 60.0 ± 10.0 years). FIELD STRENGTH/SEQUENCE T2WI, T1WI, multi-b value DWI, MR-based attenuation correction, and PET imaging on a 3.0 T whole-body PET/MR system. ASSESSMENT The apparent diffusion coefficient (ADC), RSI-derived parameters (restricted diffusionf 1 , hindered diffusionf 2 , and free diffusionf 3 ) and the maximum standardized uptake value (SUVmax) were calculated and analyzed for diagnostic efficacy individually or in combination. STATISTICAL TESTS Student's t-test, Mann-Whitney U test, receiver operating characteristic (ROC) curves, Delong test, Spearman's correlation analysis. P < 0.05 was considered statistically significant. RESULTS Thef 1 , SUVmax were significantly higher, andf 3 , ADC were significantly lower in the malignant group [0.717 ± 0.131, 9.125 (5.753, 13.058), 0.194 ± 0.099, 1.240 (0.972, 1.407)] compared to the benign group [0.504 ± 0.236, 3.390 (1.673, 6.030), 0.398 ± 0.195, 1.485 ± 0.382]. The area under the ROC curve (AUC) values ranked from highest to lowest as follows: AUC (SUVmax) > AUC (f 3 ) > AUC (f 1 ) > AUC (ADC) > AUC (f 2 ) (AUC = 0.819, 0.811, 0.770, 0.745, 0549). The AUC (AUC = 0.900) of the combined model of RSI with PET was significantly higher than that of either single-modality imaging. CONCLUSION RSI-derived parameters (f 1 ,f 3 ) might help to distinguish primary benign and malignant lung lesions and the discriminatory utility off 2 was not observed. The RSI exhibits comparable or potentially enhanced performance compared with DWI, and the combined RSI and PET model might improve diagnostic efficacy. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Xue Liu
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Nan Meng
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Yihang Zhou
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Xinxiang Medical University Henan Provincial People's Hospital, Zhengzhou, China
| | - Fangfang Fu
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, United Imaging Healthcare Group, Beijing, China
| | - Zhongyan Xiong
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Chao Zou
- Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Meiyun Wang
- Department of Medical Imaging, Zhengzhou University People's Hospital, Zhengzhou, China
- Department of Medical Imaging, Henan Provincial People's Hospital, Zhengzhou, China
- Laboratory of Brain Science and Brain-Like Intelligence Technology, Biomedical Research Institute, Henan Academy of Sciences, Zhengzhou, China
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Schelhaas S, Frohwein LJ, Wachsmuth L, Hermann S, Faber C, Schäfers KP, Jacobs AH. Voxel-Based Analysis of the Relation of 3'-Deoxy-3'-[ 18F]fluorothymidine ([ 18F]FLT) PET and Diffusion-Weighted (DW) MR Signals in Subcutaneous Tumor Xenografts Does Not Reveal a Direct Spatial Relation of These Two Parameters. Mol Imaging Biol 2022; 24:359-364. [PMID: 34755247 PMCID: PMC9085704 DOI: 10.1007/s11307-021-01673-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 10/19/2021] [Accepted: 10/20/2021] [Indexed: 10/26/2022]
Abstract
PURPOSE Multimodal molecular imaging allows a direct coregistration of different images, facilitating analysis of the spatial relation of various imaging parameters. Here, we further explored the relation of proliferation, as measured by [18F]FLT PET, and water diffusion, as an indicator of cellular density and cell death, as measured by diffusion-weighted (DW) MRI, in preclinical tumor models. We expected these parameters to be negatively related, as highly proliferative tissue should have a higher density of cells, hampering free water diffusion. PROCEDURES Nude mice subcutaneously inoculated with either lung cancer cells (n = 11 A549 tumors, n = 20 H1975 tumors) or colorectal cancer cells (n = 13 Colo205 tumors) were imaged with [18F]FLT PET and DW-MRI using a multimodal bed, which was transferred from one instrument to the other within the same imaging session. Fiducial markers allowed coregistration of the images. An automatic post-processing was developed in MATLAB handling the spatial registration of DW-MRI (measured as apparent diffusion coefficient, ADC) and [18F]FLT image data and subsequent voxel-wise analysis of regions of interest (ROIs) in the tumor. RESULTS Analyses were conducted on a total of 76 datasets, comprising a median of 2890 data points (ranging from 81 to 13,597). Scatterplots showing [18F]FLT vs. ADC values displayed various grades of relations (Pearson correlation coefficient (PCC) varied from - 0.58 to 0.49, median: -0.07). When relating PCC to tumor volume (median: 46 mm3, range: 3 mm3 to 584 mm3), lung tumors tended to have a more pronounced negative spatial relation of [18F]FLT and ADC with increasing tumor size. However, due to the low number of large tumors (> ~ 200 mm3), this conclusion has to be treated with caution. CONCLUSIONS A spatial relation of water diffusion, as measured by DW-MRI, and cellular proliferation, as measured by [18F]FLT PET, cannot be detected in the experimental datasets investigated in this study.
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Affiliation(s)
- Sonja Schelhaas
- European Institute for Molecular Imaging (EIMI), Westfälische Wilhelms-Universität Münster, Waldeyerstr. 15, 48149, Münster, Germany.
| | - Lynn Johann Frohwein
- European Institute for Molecular Imaging (EIMI), Westfälische Wilhelms-Universität Münster, Waldeyerstr. 15, 48149, Münster, Germany
| | - Lydia Wachsmuth
- Translational Research Imaging Center, Clinic of Radiology, University Hospital of Münster, Münster, Germany
| | - Sven Hermann
- European Institute for Molecular Imaging (EIMI), Westfälische Wilhelms-Universität Münster, Waldeyerstr. 15, 48149, Münster, Germany
| | - Cornelius Faber
- Translational Research Imaging Center, Clinic of Radiology, University Hospital of Münster, Münster, Germany
| | - Klaus P Schäfers
- European Institute for Molecular Imaging (EIMI), Westfälische Wilhelms-Universität Münster, Waldeyerstr. 15, 48149, Münster, Germany
| | - Andreas H Jacobs
- European Institute for Molecular Imaging (EIMI), Westfälische Wilhelms-Universität Münster, Waldeyerstr. 15, 48149, Münster, Germany
- Department of Geriatric Medicine, Johanniter Hospital, Bonn, Germany
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Fowler AM, Strigel RM. Clinical advances in PET-MRI for breast cancer. Lancet Oncol 2022; 23:e32-e43. [PMID: 34973230 PMCID: PMC9673821 DOI: 10.1016/s1470-2045(21)00577-5] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 09/20/2021] [Accepted: 10/01/2021] [Indexed: 01/03/2023]
Abstract
Imaging is paramount for the early detection and clinical staging of breast cancer, as well as to inform management decisions and direct therapy. PET-MRI is a quantitative hybrid imaging technology that combines metabolic and functional PET data with anatomical detail and functional perfusion information from MRI. The clinical applicability of PET-MRI for breast cancer is an active area of research. In this Review, we discuss the rationale and summarise the clinical evidence for the use of PET-MRI in the diagnosis, staging, prognosis, tumour phenotyping, and assessment of treatment response in breast cancer. The continued development and approval of targeted radiopharmaceuticals, together with radiomics and automated analysis tools, will further expand the opportunity for PET-MRI to provide added value for breast cancer imaging and patient care.
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Affiliation(s)
- Amy M Fowler
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, Madison, WI, USA.
| | - Roberta M Strigel
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, Madison, WI, USA
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4
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Huang Z, Li X, Wang Z, Meng N, Fu F, Han H, Li D, Bai Y, Wei W, Fang T, Feng P, Yuan J, Yang Y, Wang M. Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma. J Magn Reson Imaging 2021; 56:63-74. [PMID: 34888990 DOI: 10.1002/jmri.28010] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 11/18/2021] [Accepted: 11/18/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma. PURPOSE To explore the value of simultaneous 18 F-fluorodeoxyglucose (18 F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters. STUDY TYPE Prospective. POPULATION Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI. FIELD STRENGTH/SEQUENCE 3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and 18 F-FDG PET. ASSESSMENT DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUVmax ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed. STATISTICAL TESTS Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant. RESULTS The SUVmax , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUVmax , and MTV independently predicted the Ki-67 PI status. The combination of D, SUVmax , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUVmax (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUVmax , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733). DATA CONCLUSION The combination of D, SUVmax , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Zhun Huang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Xiaochen Li
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Zhixue Wang
- Department of Radiology, The First Affiliated Hospital of Henan University, Kaifeng, China
| | - Nan Meng
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Fangfang Fu
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Dujuan Li
- Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Yan Bai
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Wei Wei
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Ting Fang
- Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
| | - Pengyang Feng
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China
| | - Jianmin Yuan
- Central Research Institute, UIH Group, Shanghai, China
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China.,Henan Key Laboratory for Medical Imaging of Neurological Diseases, Zhengzhou, China.,Department of Medical imaging, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, China
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Iima M, Honda M, Sigmund EE, Ohno Kishimoto A, Kataoka M, Togashi K. Diffusion MRI of the breast: Current status and future directions. J Magn Reson Imaging 2020; 52:70-90. [PMID: 31520518 DOI: 10.1002/jmri.26908] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 08/12/2019] [Indexed: 12/30/2022] Open
Abstract
Diffusion-weighted imaging (DWI) is increasingly being incorporated into routine breast MRI protocols in many institutions worldwide, and there are abundant breast DWI indications ranging from lesion detection and distinguishing malignant from benign tumors to assessing prognostic biomarkers of breast cancer and predicting treatment response. DWI has the potential to serve as a noncontrast MR screening method. Beyond apparent diffusion coefficient (ADC) mapping, which is a commonly used quantitative DWI measure, advanced DWI models such as intravoxel incoherent motion (IVIM), non-Gaussian diffusion MRI, and diffusion tensor imaging (DTI) are extensively exploited in this field, allowing the characterization of tissue perfusion and architecture and improving diagnostic accuracy without the use of contrast agents. This review will give a summary of the clinical literature along with future directions. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;52:70-90.
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Affiliation(s)
- Mami Iima
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Department of Clinical Innovative Medicine, Institute for Advancement of Clinical and Translational Science, Kyoto University Hospital, Kyoto, Japan
| | - Maya Honda
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Eric E Sigmund
- Department of Radiology, NYU Langone Health, New York, New York, USA
- Center for Advanced Imaging and Innovation (CAI2R), New York, New York, USA
| | - Ayami Ohno Kishimoto
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Masako Kataoka
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kaori Togashi
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Xu C, Du S, Zhang S, Wang B, Dong C, Sun H. Value of integrated PET-IVIM MR in assessing metastases in hypermetabolic pelvic lymph nodes in cervical cancer: a multi-parameter study. Eur Radiol 2020; 30:2483-2492. [PMID: 32040728 DOI: 10.1007/s00330-019-06611-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Revised: 11/13/2019] [Accepted: 12/06/2019] [Indexed: 02/07/2023]
Abstract
PURPOSE To evaluate the value of integrated multi-parameter positron emission tomography-intravoxel incoherent motion magnetic resonance (PET-IVIM MR) imaging for pelvic lymph nodes with high FDG uptake in cervical cancer, and to determine the best combination of parameters. METHODS A total of 38 patients with 59 lymph nodes with high FDG uptake were included. The imaging parameters of the lymph nodes were calculated by PET-IVIM MR, and the differences between lymph nodes diagnosed by postoperative pathology as metastasis versus non-metastasis were compared. We used the receiver operating characteristic (ROC) curve and logistic regression to construct a combination prediction model to filter low value and similar parameters, in order to search the optimal combination of PET/MR parameters for predicting pathologically confirmed metastatic lymph nodes. The correlation between diffusion parameters and metabolic parameters was analyzed by Spearman's rank correlation. RESULTS The maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), total metabolic tumor volume (MTV), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC), diffusion-related coefficient (D), and perfusion-related parameter (F) showed significant differences between the metastatic and non-metastatic groups (p < 0.05). The combination of MTV, SUVmax, and D had the strongest predictive value (area under the ROC 0.983, p < 0.05). SUVmax, SUVmean, and TLG weakly correlated with F (R = - 0.306, - 0.290, and - 0.310; p < 0.05). CONCLUSIONS The combination of MTV, SUVmax, and D may have a better diagnostic performance than PET- or IVIM-derived parameters either in combination or individually. No strong correlation exists between diffusion parameters and metabolic parameters. KEY POINTS • Integrated PET-IVIM MR may assist to characterize lymph node status. • The combination of MTV, SUVmax, and D may have a better diagnostic performance than PET- or IVIM-derived parameters either in combination or individually for the assessment of pelvic lymph nodes with high FDG uptake. • No strong correlation exists between diffusion parameters and metabolic parameters in pelvic lymph nodes with high FDG uptake.
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Affiliation(s)
- Chen Xu
- Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China.,Liaoning Provincial Key Laboratory of Medical Imaging, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China
| | - Siyao Du
- Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China
| | - Siyu Zhang
- Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China
| | - Bo Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China
| | | | - Hongzan Sun
- Department of Radiology, Shengjing Hospital of China Medical University, Sanhao Street No 36, Heping District, Shenyang, 110004, Liaoning, China.
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Schawkat K, Sah BR, Ter Voert EE, Delso G, Wurnig M, Becker AS, Leibl S, Schneider PM, Reiner CS, Huellner MW, Veit-Haibach P. Role of intravoxel incoherent motion parameters in gastroesophageal cancer: relationship with 18F-FDG-positron emission tomography, computed tomography perfusion and magnetic resonance perfusion imaging parameters. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2019; 65:178-186. [PMID: 31496202 DOI: 10.23736/s1824-4785.19.03153-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Identification of pretherapeutic predictive markers in gastro-esophageal cancer is essential for individual-oriented treatment. This study evaluated the relationship of multimodality parameters derived from intravoxel incoherent motion method (IVIM), 18F-FDG-positron emission tomography (PET), computed tomography (CT) perfusion and dynamic contrast enhanced magnetic resonance imaging (MRI) in patients with gastro-esophageal cancer and investigated their histopathological correlation. METHODS Thirty-one consecutive patients (28 males; median age 63.9 years; range 37-84 years) with gastro-esophageal adenocarcinoma (N.=22) and esophageal squamous cell carcinoma (N.=9) were analyzed. IVIM parameters: pseudodiffusion (D*), perfusion fraction (fp), true diffusion (D) and the threshold b-value (bval); PET-parameters: SUV<inf>max</inf>, metabolic tumor volume (MTV) and total lesion glycolysis (TLG); CT perfusion parameters: blood flow (BF), blood volume (BV) and mean transit time (MTT); and MR perfusion parameters: time to enhance, positive enhancement integral, time-to-peak (TTP), maximum-slope-of-increase, and maximum-slope-of-decrease were determined, and correlated to each other and to histopathology. RESULTS IVIM and PET parameters showed significant negative correlations: MTV and bval (r<inf>s</inf> =-0.643, P=0.002), TLG and bval (r<inf>s</inf>=-0.699, P<0.01) and TLG and fp (r<inf>s</inf>=-0.577, P=0.006). Positive correlation was found for TLG and D (r<inf>s</inf>=0.705, P=0.000). Negative correlation was found for bval and staging (r<inf>s</inf>=0.590, P=0.005). Positive correlation was found for positive enhancement interval and BV (r<inf>s</inf>=0.547, P=0.007), BF and regression index (r<inf>s</inf>=0.753, P=0.005) and for time-to-peak and staging (r<inf>s</inf>=0.557, P=0.005). CONCLUSIONS IVIM parameters (bval, fp, D) provide quantitative information and correlate with PET parameters (MTV, TLG) and staging. IVIM might be a useful tool for additional characterization of gastro-esophageal cancer.
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Affiliation(s)
- Khoschy Schawkat
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland - .,University of Zurich, Zurich, Switzerland -
| | - Bert-Ram Sah
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Edwin E Ter Voert
- University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Gaspar Delso
- Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Moritz Wurnig
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Anton S Becker
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Sebastian Leibl
- Department of Pathology, University Hospital Zurich, Zurich, Switzerland
| | - Paul M Schneider
- Center for Visceral, Thoracic and Specialized Tumor Surgery, Hirslanden Medical Center, Zurich, Switzerland
| | - Cäcilia S Reiner
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland
| | - Martin W Huellner
- University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland
| | - Patrick Veit-Haibach
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.,University of Zurich, Zurich, Switzerland.,Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland.,University of Toronto, Toronto, ON, Canada.,Toronto Joint Department of Medical Imaging, University Hospital of Zurich, Toronto General Hospital, Zurich, Switzerland
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8
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Leithner D, Horvat JV, Bernard-Davila B, Helbich TH, Ochoa-Albiztegui RE, Martinez DF, Zhang M, Thakur SB, Wengert GJ, Staudenherz A, Jochelson MS, Morris EA, Baltzer PAT, Clauser P, Kapetas P, Pinker K. A multiparametric [ 18F]FDG PET/MRI diagnostic model including imaging biomarkers of the tumor and contralateral healthy breast tissue aids breast cancer diagnosis. Eur J Nucl Med Mol Imaging 2019; 46:1878-1888. [PMID: 31197455 PMCID: PMC6647078 DOI: 10.1007/s00259-019-04331-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/03/2019] [Indexed: 02/03/2023]
Abstract
Purpose To develop a multiparametric [18F]FDG positron emission tomography/magnetic resonance imaging (PET/MRI) model for breast cancer diagnosis incorporating imaging biomarkers of breast tumors and contralateral healthy breast tissue. Methods In this prospective study and retrospective data analysis, 141 patients (mean 57 years) with an imaging abnormality detected on mammography and/or ultrasound (BI-RADS 4/5) underwent combined multiparametric [18F]FDG PET/MRI with PET/computed tomography and multiparametric MRI of the breast at 3 T. Images were evaluated and the following were recorded: for the tumor, BI-RADS descriptors on dynamic contrast-enhanced (DCE)-MRI, mean apparent diffusion co-efficient (ADCmean) on diffusion-weighted imaging (DWI), and maximum standard uptake value (SUVmax) on [18F]FDG-PET; and for the contralateral healthy breast, background parenchymal enhancement (BPE) and amount of fibroglandular tissue (FGT) on DCE-MRI, ADCmean on DWI, and SUVmax. Histopathology served as standard of reference. Uni-, bi-, and multivariate logistic regression analyses were performed to assess the relationships between malignancy and imaging features. Predictive discrimination of benign and malignant breast lesions was examined using area under the receiver operating characteristic curve (AUC). Results There were 100 malignant and 41 benign lesions (size: median 1.9, range 0.5–10 cm). The multivariate regression model incorporating significant univariate predictors identified tumor enhancement kinetics (P = 0.0003), tumor ADCmean (P < 0.001), and BPE of the contralateral healthy breast (P = 0.0019) as independent predictors for breast cancer diagnosis. Other biomarkers did not reach significance. Combination of the three significant biomarkers achieved an AUC value of 0.98 for breast cancer diagnosis. Conclusion A multiparametric [18F]FDG PET/MRI diagnostic model incorporating both qualitative and quantitative parameters of the tumor and the healthy contralateral tissue aids breast cancer diagnosis.
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Affiliation(s)
- Doris Leithner
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
- Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt, Germany
| | - Joao V Horvat
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Blanca Bernard-Davila
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thomas H Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - R Elena Ochoa-Albiztegui
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Danny F Martinez
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Michelle Zhang
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Sunitha B Thakur
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Georg J Wengert
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - Anton Staudenherz
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
| | - Maxine S Jochelson
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Elizabeth A Morris
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - Paola Clauser
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - Katja Pinker
- Department of Radiology, Breast Imaging Service, Memorial Sloan Kettering Cancer Center, 300 E 66th St, 7th Floor, New York, NY, 10065, USA.
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria.
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Pujara AC, Kim E, Axelrod D, Melsaether AN. PET/MRI in Breast Cancer. J Magn Reson Imaging 2018; 49:328-342. [DOI: 10.1002/jmri.26298] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 07/30/2018] [Accepted: 07/31/2018] [Indexed: 12/12/2022] Open
Affiliation(s)
- Akshat C. Pujara
- Department of Radiology, Division of Breast Imaging; University of Michigan Health System; Ann Arbor Michigan USA
| | - Eric Kim
- Department of Radiology; NYU School of Medicine; New York New York USA
| | - Deborah Axelrod
- Department of Surgery; Perlmutter Cancer Center, NYU School of Medicine; New York New York USA
| | - Amy N. Melsaether
- Department of Radiology; NYU School of Medicine; New York New York USA
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