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Luo Y, Zhu M, Wei X, Xu J, Pan S, Liu G, Song Y, Hu W, Dai Y, Wu G. Investigation of clear cell renal cell carcinoma grades using diffusion-relaxation correlation spectroscopic imaging with optimized spatial-spectrum analysis. Br J Radiol 2024; 97:135-141. [PMID: 38263829 PMCID: PMC11008501 DOI: 10.1093/bjr/tqad003] [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: 06/12/2023] [Revised: 09/28/2023] [Accepted: 10/10/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVES To differentiate high-grade from low-grade clear cell renal cell carcinoma (ccRCC) using diffusion-relaxation correlation spectroscopic imaging (DR-CSI) spectra in an equal separating analysis. METHODS Eighty patients with 86 pathologically confirmed ccRCCs who underwent DR-CSI were enrolled. Two radiologists delineated the region of interest. The spectrum was derived based on DR-CSI and was further segmented into multiple equal subregions from 2*2 to 9*9. The agreement between the 2 radiologists was assessed by the intraclass correlation coefficient (ICC). Logistic regression was used to establish the regression model for differentiation, and 5-fold cross-validation was used to evaluate its accuracy. McNemar's test was used to compare the diagnostic performance between equipartition models and the traditional parameters, including the apparent diffusion coefficient (ADC) and T2 value. RESULTS The inter-reader agreement decreased as the divisions in the equipartition model increased (overall ICC ranged from 0.859 to 0.920). The accuracy increased from the 2*2 to 9*9 equipartition model (0.68 for 2*2, 0.69 for 3*3 and 4*4, 0.70 for 5*5, 0.71 for 6*6, 0.78 for 7*7, and 0.75 for 8*8 and 9*9). The equipartition models with divisions >7*7 were significantly better than ADC and T2 (vs ADC: P = .002-.008; vs T2: P = .001-.004). CONCLUSIONS The equipartition method has the potential to analyse the DR-CSI spectrum and discriminate between low-grade and high-grade ccRCC. ADVANCES IN KNOWLEDGE The evaluation of DR-CSI relies on prior knowledge, and how to assess the spectrum derived from DR-CSI without prior knowledge has not been well studied.
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Affiliation(s)
- Yuansheng Luo
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Mengying Zhu
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaobin Wei
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Jianrong Xu
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Shihang Pan
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Guiqin Liu
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yang Song
- MR Scientific Marketing, Siemens Healthineers Ltd., 200129 Shanghai, China
| | - Wentao Hu
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yongming Dai
- School of Biomedical Engineering, Shanghai Tech University, 201210 Shanghai, China
| | - Guangyu Wu
- Department of Radiology, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai, China
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2
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Jin B, Yang J, Zhen J, Xu Y, Wang C, Jing Q, Shang Y. Intravoxel Incoherent Motion and Dynamic Contrast-Enhanced Magnetic Resonance Imaging Can Differentiate Between Atypical Cartilaginous Tumors and High-Grade Chondrosarcoma: Correlation With Histological Vessel Characteristics. J Comput Assist Tomogr 2024; 48:123-128. [PMID: 37558644 DOI: 10.1097/rct.0000000000001515] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/11/2023]
Abstract
OBJECTIVE To differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma of the major long bones using intravoxel incoherent motion (IVIM) and Dynamic Contrast-Enhanced magnetic resonance imaging (DCE-MRI), and explore the correlation of quantitative parameters with hypoxia inducible factor-1α (HIF-1α), vascular endothelial growth factor (VEGF) and microvessel density (MVD). METHOD Between September 2016 and March 2022, 35 patients (17 atypical cartilaginous tumors, 18 high-grade chondrosarcoma) underwent MRI examination and pathological confirmation at our hospital. First, IVIM-derived parameters ( D , D* , and f ), and DCE-MRI parameters ( Ktrans , Kep , and V e ) were measured, and intraclass correlation efficient (ICC) and Mann-Whitney U test were performed. Second, receiver-operating characteristic curve analysis was performed to evaluate the diagnostic performance. Finally, Spearman's correlation analysis was performed between the quantitative parameters of IVIM-DWI and DCE-MRI and the immunohistochemical factors HIF-1α, VEGF, and MVD in chondrosarcoma tissue. RESULTS D in atypical cartilaginous tumors was significantly higher than that in high-grade chondrosarcoma ( P = 0.003), whereas D* , Ktrans , and K ep in atypical cartilaginous tumors were significantly lower than those in high-grade chondrosarcoma (all P < 0.001). Ktrans demonstrated the highest area under the curve (AUC) of 0.979. The D* , Ktrans , and K ep were positively correlated with HIF-1α, VEGF, and MVD (all P < 0.001), whereas D had no correlation with HIF-1α, VEGF, and MVD ( P = 0.113, 0.077, 0.058, respectively). CONCLUSION The IVIM-DWI quantitative parameters ( D , D* ) and DCE-MRI quantitative parameters ( Ktrans , Kep ) are helpful to differentiate between atypical cartilaginous tumors and high-grade chondrosarcoma and could be imaging biomarkers to reflect the expressions of HIF-1α, VEGF, and angiogenesis of chondrosarcoma.
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Affiliation(s)
- Bo Jin
- From the Department of Radiology, Children's Hospital of Shanxi
| | - Jie Yang
- Department of Radiology, Shanxi Traditional Chinese Medical Hospital
| | | | - Yang Xu
- Department of Imaging and Nuclear Medicine, College of Medical Imaging, Shanxi Medical University
| | - Chen Wang
- Department of Pathology, Shanxi Medical University Second Affiliated Hospital
| | - Qing Jing
- Department of Biochemistry and Molecular Biology, College of Basic Medicine, Shanxi Medical University, Taiyuan, Shanxi Province, China
| | - Yangwei Shang
- Department of Pathology, Shanxi Medical University Second Affiliated Hospital
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Tao J, Yin Z, Li X, Zhang Y, Zhang K, Yang Y, Fang S, Wang S. Correlation between IVIM parameters and microvessel architecture: direct comparison of MRI images and pathological slices in an orthotopic murine model of rhabdomyosarcoma. Eur Radiol 2023; 33:8576-8584. [PMID: 37368112 DOI: 10.1007/s00330-023-09835-2] [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: 04/30/2022] [Revised: 03/20/2023] [Accepted: 04/14/2023] [Indexed: 06/28/2023]
Abstract
OBJECTIVE This study aimed to explore the correlation between intravoxel incoherent motion (IVIM) parameters and microvessel architecture (microvessel density (MVD), vasculogenic mimicry (VM), and pericyte coverage index (PCI)) in an orthotopic murine model of rhabdomyosarcoma. METHODS The murine model was established by injecting rhabdomyosarcoma-derived (RD) cells into the muscle. Nude mice underwent routine magnetic resonance imaging (MRI) and IVIM examinations with ten b values (0, 50, 100, 150, 200, 400, 600, 800, 1000, and 2000 s/mm2). D, D*, and f values were calculated with the ADW4.7 workstation. MRI images and pathological slices were directly compared to ensure that radiology parameters accurately reflect pathology. MVD, VM, PCI, and cellularity were obtained by histological analysis. The correlations were assessed between IVIM parameters (D, D*, f, and fD* values) and pathological markers (MVD, VM, PCI, and cellularity). RESULTS The average of D, D*, f, and fD* values were 0.55 ± 0.07 × 10-3 mm2/s, 5.25 ± 0.73 × 10-3 mm2/s, 13.39 ± 7.68%, and 0.73 ± 0.49 × 10-3 mm2/s, respectively. The average of MVD, VM, PCI, and cellularity were 41.91 ± 10.98, 1.16 ± 0.83, 0.49 ± 0.18, and 39.15 ± 9.00%. D*, f, and fD* values showed a positive correlation with MVD separately, while the D value did not correlate with MVD. D value negatively correlated to VM moderately, and other parameters did not associate with VM. D* and fD* values were positively correlated with PCI, but no correlation was observed between other parameters and PCI. CONCLUSIONS IVIM may evaluate the tumor microvessel architecture. D*, f, and fD* may reflect the endothelial lining blood vessel; D could indirectly reflect the VM; D* and fD* could reflect PCI(the normal degree of the tumor blood vessel). CLINICAL RELEVANCE STATEMENT An intravoxel incoherent motion may be useful in assessing rhabdomyosarcoma microvessel structure to predict the target and effectiveness of anti-angiogenic therapy. KEY POINTS • IVIM may be used to evaluate the tumor microvessel architecture in the mouse rhabdomyosarcoma model. • The MRI-pathology control method achieves correspondence between MRI slices and pathology slices, which ensures the consistency of the ROI of MRI and the pathology observation region.
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Affiliation(s)
- Juan Tao
- Department of Pathology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, China
| | - Zhenzhen Yin
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Xiangwen Li
- Department of Radiology and Institute of Medical Functional and Molecular Imaging, Huashan Hospital, Fudan University, 12 Wulumuqizhong Road, Shanghai, China
| | - Yu Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Kai Zhang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Yanyu Yang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Shaobo Fang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China
| | - Shaowu Wang
- Department of Radiology, The Second Hospital, Dalian Medical University, 467 Zhongshan Road, Dalian, 116027, China.
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4
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Fokkinga E, Hernandez-Tamames JA, Ianus A, Nilsson M, Tax CMW, Perez-Lopez R, Grussu F. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging 2023. [PMID: 38032021 DOI: 10.1002/jmri.29144] [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: 08/11/2023] [Revised: 10/30/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023] Open
Abstract
Diffusion-weighted magnetic resonance imaging (DW-MRI) aims to disentangle multiple biological signal sources in each imaging voxel, enabling the computation of innovative maps of tissue microstructure. DW-MRI model development has been dominated by brain applications. More recently, advanced methods with high fidelity to histology are gaining momentum in other contexts, for example, in oncological applications of body imaging, where new biomarkers are urgently needed. The objective of this article is to review the state-of-the-art of DW-MRI in body imaging (ie, not including the nervous system) in oncology, and to analyze its value as compared to reference colocalized histology measurements, given that demonstrating the histological validity of any new DW-MRI method is essential. In this article, we review the current landscape of DW-MRI techniques that extend standard apparent diffusion coefficient (ADC), describing their acquisition protocols, signal models, fitting settings, microstructural parameters, and relationship with histology. Preclinical, clinical, and in/ex vivo studies were included. The most used techniques were intravoxel incoherent motion (IVIM; 36.3% of used techniques), diffusion kurtosis imaging (DKI; 16.7%), vascular, extracellular, and restricted diffusion for cytometry in tumors (VERDICT; 13.3%), and imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED; 11.7%). Another notable category of techniques relates to innovative b-tensor diffusion encoding or joint diffusion-relaxometry. The reviewed approaches provide histologically meaningful indices of cancer microstructure (eg, vascularization/cellularity) which, while not necessarily accurate numerically, may still provide useful sensitivity to microscopic pathological processes. Future work of the community should focus on improving the inter-/intra-scanner robustness, and on assessing histological validity in broader contexts. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ella Fokkinga
- Biomedical Engineering, Track Medical Physics, Delft University of Technology, Delft, The Netherlands
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Andrada Ianus
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Markus Nilsson
- Department of Diagnostic Radiology, Clinical Sciences Lund, Lund, Sweden
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Raquel Perez-Lopez
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Francesco Grussu
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
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5
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Zhou Z, Qian X, Hu J, Geng C, Zhang Y, Dou X, Che T, Zhu J, Dai Y. Multi-phase-combined CECT radiomics models for Fuhrman grade prediction of clear cell renal cell carcinoma. Front Oncol 2023; 13:1167328. [PMID: 37692840 PMCID: PMC10485140 DOI: 10.3389/fonc.2023.1167328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 07/24/2023] [Indexed: 09/12/2023] Open
Abstract
Objective This study aimed to evaluate the effectiveness of multi-phase-combined contrast-enhanced CT (CECT) radiomics methods for noninvasive Fuhrman grade prediction of clear cell renal cell carcinoma (ccRCC). Methods A total of 187 patients with four-phase CECT images were retrospectively enrolled and then were categorized into training cohort (n=126) and testing cohort (n=61). All patients were confirmed as ccRCC by histopathological reports. A total of 110 3D classical radiomics features were extracted from each phase of CECT for individual ccRCC lesion, and contrast-enhanced variation features were also calculated as derived radiomics features. These features were concatenated together, and redundant features were removed by Pearson correlation analysis. The discriminative features were selected by minimum redundancy maximum relevance method (mRMR) and then input into a C-support vector classifier to build multi-phase-combined CECT radiomics models. The prediction performance was evaluated by the area under the curve (AUC) of receiver operating characteristic (ROC). Results The multi-phase-combined CECT radiomics model showed the best prediction performance (AUC=0.777) than the single-phase CECT radiomics model (AUC=0.711) in the testing cohort (p value=0.039). Conclusion The multi-phase-combined CECT radiomics model is a potential effective way to noninvasively predict Fuhrman grade of ccRCC. The concatenation of first-order features and texture features extracted from corticomedullary phase and nephrographic phase are discriminative feature representations.
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Affiliation(s)
- Zhiyong Zhou
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China
| | - Xusheng Qian
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou, Jiangsu, China
| | - Jisu Hu
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou, Jiangsu, China
| | - Chen Geng
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China
| | - Yongsheng Zhang
- Department of Pathology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Xin Dou
- Department of Radiology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Tuanjie Che
- Key Laboratory of Functional Genomic and Molecular Diagnosis of Gansu Province, Lanzhou, Gansu, China
- Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Jianbing Zhu
- Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, Jiangsu, China
| | - Yakang Dai
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, China
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6
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Pedrosa I, Cadeddu JA. How We Do It: Managing the Indeterminate Renal Mass with the MRI Clear Cell Likelihood Score. Radiology 2021; 302:256-269. [PMID: 34904873 PMCID: PMC8805575 DOI: 10.1148/radiol.210034] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
The widespread use of cross-sectional imaging has led to a continuous increase in the number of incidentally detected indeterminate renal masses. Frequently, these clinical scenarios involve an older patient with comorbidities and a small renal mass (≤4 cm). Despite aggressive treatment in early stages of the disease, a clear positive effect in reducing kidney cancer-specific mortality is lacking, indicating that many renal cancers exhibit an indolent oncologic behavior. Furthermore, in general, one in five small renal masses is histologically benign and may not benefit from aggressive treatment. Although active surveillance is increasingly recognized as a management option for some patients, the absence of reliable clinical and imaging predictive biologic markers of aggressiveness can contribute to patient anxiety and limit its use in clinical practice. A standardized approach to the image interpretation of solid renal masses has not been broadly implemented. The clear cell likelihood score (ccLS) derived from multiparametric MRI is useful in noninvasively identifying the clear cell subtype, the most common and aggressive form of kidney cancer. Herein, a review of the ccLS is presented, including a step-by-step guide for image interpretation and additional guidance for its implementation in clinical practice.
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Affiliation(s)
- Ivan Pedrosa
- From the Department of Radiology (I.P., J.A.C.), Department of Urology (I.P., J.A.C.), and Advanced Imaging Research Center (I.P.), University of Texas Southwestern, 5323 Harry Hines Blvd, Clements Imaging Bldg, Ste 2202, MC 9085, Dallas, TX 75390
| | - Jeffrey A. Cadeddu
- From the Department of Radiology (I.P., J.A.C.), Department of Urology (I.P., J.A.C.), and Advanced Imaging Research Center (I.P.), University of Texas Southwestern, 5323 Harry Hines Blvd, Clements Imaging Bldg, Ste 2202, MC 9085, Dallas, TX 75390
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7
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Hernando D, Zhang Y, Pirasteh A. Quantitative diffusion MRI of the abdomen and pelvis. Med Phys 2021; 49:2774-2793. [PMID: 34554579 DOI: 10.1002/mp.15246] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/05/2021] [Accepted: 09/15/2021] [Indexed: 12/14/2022] Open
Abstract
Diffusion MRI has enormous potential and utility in the evaluation of various abdominal and pelvic disease processes including cancer and noncancer imaging of the liver, prostate, and other organs. Quantitative diffusion MRI is based on acquisitions with multiple diffusion encodings followed by quantitative mapping of diffusion parameters that are sensitive to tissue microstructure. Compared to qualitative diffusion-weighted MRI, quantitative diffusion MRI can improve standardization of tissue characterization as needed for disease detection, staging, and treatment monitoring. However, similar to many other quantitative MRI methods, diffusion MRI faces multiple challenges including acquisition artifacts, signal modeling limitations, and biological variability. In abdominal and pelvic diffusion MRI, technical acquisition challenges include physiologic motion (respiratory, peristaltic, and pulsatile), image distortions, and low signal-to-noise ratio. If unaddressed, these challenges lead to poor technical performance (bias and precision) and clinical outcomes of quantitative diffusion MRI. Emerging and novel technical developments seek to address these challenges and may enable reliable quantitative diffusion MRI of the abdomen and pelvis. Through systematic validation in phantoms, volunteers, and patients, including multicenter studies to assess reproducibility, these emerging techniques may finally demonstrate the potential of quantitative diffusion MRI for abdominal and pelvic imaging applications.
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Affiliation(s)
- Diego Hernando
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Yuxin Zhang
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Ali Pirasteh
- Departments of Radiology and Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
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8
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Udayakumar D, Zhang Z, Xi Y, Dwivedi DK, Fulkerson M, Haldeman S, McKenzie T, Yousuf Q, Joyce A, Hajibeigi A, Notgrass H, de Leon AD, Yuan Q, Lewis MA, Madhuranthakam AJ, Sibley RC, Elias R, Guo J, Christie A, McKay RM, Cadeddu JA, Bagrodia A, Margulis V, Brugarolas J, Wang T, Kapur P, Pedrosa I. Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform. Clin Cancer Res 2021; 27:4794-4806. [PMID: 34210685 DOI: 10.1158/1078-0432.ccr-21-0706] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 06/02/2021] [Accepted: 06/24/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell carcinoma (ccRCC) and is a confounding factor for therapy selection. Most approaches to evaluate ITH are limited by two-dimensional ex vivo tissue analyses. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can noninvasively assess the spatial landscape of entire tumors in their natural milieu. To assess the potential of DCE-MRI, we developed a vertically integrated radiogenomics colocalization approach for multi-region tissue acquisition and analyses. We investigated the potential of spatial imaging features to predict molecular subtypes using histopathologic and transcriptome correlatives. EXPERIMENTAL DESIGN We report the results of a prospective study of 49 patients with ccRCC who underwent DCE-MRI prior to nephrectomy. Surgical specimens were sectioned to match the MRI acquisition plane. RNA sequencing data from multi-region tumor sampling (80 samples) were correlated with percent enhancement on DCE-MRI in spatially colocalized regions of the tumor. Independently, we evaluated clinical applicability of our findings in 19 patients with metastatic RCC (39 metastases) treated with first-line antiangiogenic drugs or checkpoint inhibitors. RESULTS DCE-MRI identified tumor features associated with angiogenesis and inflammation, which differed within and across tumors, and likely contribute to the efficacy of antiangiogenic drugs and immunotherapies. Our vertically integrated analyses show that angiogenesis and inflammation frequently coexist and spatially anti-correlate in the same tumor. Furthermore, MRI contrast enhancement identifies phenotypes with better response to antiangiogenic therapy among patients with metastatic RCC. CONCLUSIONS These findings have important implications for decision models based on biopsy samples and highlight the potential of more comprehensive imaging-based approaches.
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Affiliation(s)
- Durga Udayakumar
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas.,Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas.,Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas
| | - Ze Zhang
- Quantitative Biomedical Research Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, Texas
| | - Yin Xi
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas.,Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, Texas
| | - Durgesh K Dwivedi
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Michael Fulkerson
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Sydney Haldeman
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Tiffani McKenzie
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas
| | - Qurratulain Yousuf
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Allison Joyce
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Asghar Hajibeigi
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Hollis Notgrass
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas
| | | | - Qing Yuan
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Matthew A Lewis
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Ananth J Madhuranthakam
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas.,Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas
| | - Robert C Sibley
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Roy Elias
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Junyu Guo
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas
| | - Alana Christie
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Renée M McKay
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Jeffrey A Cadeddu
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas.,Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Urology, UT Southwestern Medical Center, Dallas, Texas
| | - Aditya Bagrodia
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Urology, UT Southwestern Medical Center, Dallas, Texas
| | - Vitaly Margulis
- Department of Urology, UT Southwestern Medical Center, Dallas, Texas.,Institute for Urology and Reproductive Health, Sechenov University, Moscow, Russia
| | - James Brugarolas
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas
| | - Tao Wang
- Quantitative Biomedical Research Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, Texas.,Center for the Genetics of Host Defense, UT Southwestern Medical Center, Dallas, Texas
| | - Payal Kapur
- Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Pathology, UT Southwestern Medical Center, Dallas, Texas.,Department of Urology, UT Southwestern Medical Center, Dallas, Texas
| | - Ivan Pedrosa
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas. .,Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas.,Kidney Cancer Program - Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, Texas.,Department of Urology, UT Southwestern Medical Center, Dallas, Texas
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9
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Prasad S, Chandra A, Cavo M, Parasido E, Fricke S, Lee Y, D'Amone E, Gigli G, Albanese C, Rodriguez O, Del Mercato LL. Optical and magnetic resonance imaging approaches for investigating the tumour microenvironment: state-of-the-art review and future trends. NANOTECHNOLOGY 2021; 32:062001. [PMID: 33065554 DOI: 10.1088/1361-6528/abc208] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The tumour microenvironment (TME) strongly influences tumorigenesis and metastasis. Two of the most characterized properties of the TME are acidosis and hypoxia, both of which are considered hallmarks of tumours as well as critical factors in response to anticancer treatments. Currently, various imaging approaches exist to measure acidosis and hypoxia in the TME, including magnetic resonance imaging (MRI), positron emission tomography and optical imaging. In this review, we will focus on the latest fluorescent-based methods for optical sensing of cell metabolism and MRI as diagnostic imaging tools applied both in vitro and in vivo. The primary emphasis will be on describing the current and future uses of systems that can measure intra- and extra-cellular pH and oxygen changes at high spatial and temporal resolution. In addition, the suitability of these approaches for mapping tumour heterogeneity, and assessing response or failure to therapeutics will also be covered.
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Affiliation(s)
- Saumya Prasad
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Anil Chandra
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Marta Cavo
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Erika Parasido
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
| | - Stanley Fricke
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
- Department of Radiology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Yichien Lee
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Eliana D'Amone
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
- Department of Mathematics and Physics 'Ennio De Giorgi', University of Salento, via Arnesano, 73100, Lecce, Italy
| | - Chris Albanese
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
- Department of Radiology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Olga Rodriguez
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
| | - Loretta L Del Mercato
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
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10
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Dwivedi DK, Xi Y, Kapur P, Madhuranthakam AJ, Lewis MA, Udayakumar D, Rasmussen R, Yuan Q, Bagrodia A, Margulis V, Fulkerson M, Brugarolas J, Cadeddu JA, Pedrosa I. Magnetic Resonance Imaging Radiomics Analyses for Prediction of High-Grade Histology and Necrosis in Clear Cell Renal Cell Carcinoma: Preliminary Experience. Clin Genitourin Cancer 2021; 19:12-21.e1. [PMID: 32669212 PMCID: PMC7680717 DOI: 10.1016/j.clgc.2020.05.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 05/16/2020] [Accepted: 05/16/2020] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Percutaneous renal mass biopsy results can accurately diagnose clear cell renal cell carcinoma (ccRCC); however, their reliability to determine nuclear grade in larger, heterogeneous tumors is limited. We assessed the ability of radiomics analyses of magnetic resonance imaging (MRI) to predict high-grade (HG) histology in ccRCC. PATIENTS AND METHODS Seventy patients with a renal mass underwent 3 T MRI before surgery between August 2012 and August 2017. Tumor length, first-order statistics, and Haralick texture features were calculated on T2-weighted and dynamic contrast-enhanced (DCE) MRI after manual tumor segmentation. After a variable clustering algorithm was applied, tumor length, washout, and all cluster features were evaluated univariably by receiver operating characteristic curves. Three logistic regression models were constructed to assess the predictability of HG ccRCC and then cross-validated. RESULTS At univariate analysis, area under the curve values of length, and DCE texture cluster 1 and cluster 3 for diagnosis of HG ccRCC were 0.7 (95% confidence interval [CI], 0.58-0.82, false discovery rate P = .008), 0.72 (95% CI, 0.59-0.84, false discovery rate P = .004), and 0.75 (95% CI, 0.63-0.87, false discovery rate P = .0009), respectively. At multivariable analysis, area under the curve for model 1 (tumor length only), model 2 (length + DCE clusters 3 and 4), and model 3 (DCE cluster 1 and 3) for diagnosis of HG ccRCC were 0.67 (95% CI, 0.54-0.79), 0.82 (95% CI, 0.71-0.92), and 0.81 (95% CI, 0.70-0.91), respectively. CONCLUSION Radiomics analysis of MRI images was superior to tumor size for the prediction of HG histology in ccRCC in our cohort.
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Affiliation(s)
| | - Yin Xi
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX; Department of Clinical Science, UT Southwestern Medical Center, Dallas, TX
| | - Payal Kapur
- Department of Pathology, UT Southwestern Medical Center, Dallas, TX; Department of Urology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX
| | - Ananth J Madhuranthakam
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX
| | - Matthew A Lewis
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX
| | - Durga Udayakumar
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX
| | - Robert Rasmussen
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX
| | - Qing Yuan
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX
| | - Aditya Bagrodia
- Department of Urology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX
| | - Vitaly Margulis
- Department of Urology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX
| | | | - James Brugarolas
- Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX; Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX
| | - Jeffrey A Cadeddu
- Department of Urology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX
| | - Ivan Pedrosa
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX; Department of Urology, UT Southwestern Medical Center, Dallas, TX; Kidney Cancer Program, UT Southwestern Medical Center, Dallas, TX; Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX.
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11
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Tegel BR, Huber S, Savic LJ, Lin M, Gebauer B, Pollak J, Chapiro J. Quantification of contrast-uptake as imaging biomarker for disease progression of renal cell carcinoma after tumor ablation. Acta Radiol 2020; 61:1708-1716. [PMID: 32216452 DOI: 10.1177/0284185120909964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The prognosis of patients with renal cell carcinoma (RCC) depends greatly on the presence of extra-renal metastases. PURPOSE To investigate the value of total tumor volume (TTV) and enhancing tumor volume (ETV) as three-dimensional (3D) quantitative imaging biomarkers for disease aggressiveness in patients with RCC. MATERIAL AND METHODS Retrospective, HIPAA-compliant, IRB-approved study including 37 patients with RCC treated with image-guided thermal ablation during 2007-2015. TNM stage, RENAL Nephrometry Score, largest tumor diameter, TTV, and ETV were assessed on cross-sectional imaging at baseline and correlated with outcome measurements. The primary outcome was time-to-occurrence of extra-renal metastases and the secondary outcome was progression-free survival (PFS). Correlation was assessed using a Cox regression model and differences in outcomes were shown by Kaplan-Meier plots with significance and odds ratios (OR) calculated by Log-rank test/generalized Wilcoxon and continuity-corrected Woolf logit method. RESULTS Patients with a TTV or ETV > 5 cm3 were more likely to develop distant metastases compared to patients with TTV (OR 6.69, 95% confidence interval [CI] 0.33-134.4, P=0.022) or ETV (OR 8.48, 95% CI 0.42-170.1, P=0.016) < 5 cm3. Additionally, PFS was significantly worse in patients with larger ETV (P = 0.039; median PFS 51.87 months vs. 69.97 months). In contrast, stratification by median value of the established, caliper-based measurements showed no significant correlation with outcome parameters. CONCLUSION ETV, as surrogate of lesion vascularity, is a sensitive imaging biomarker for occurrence of extra-renal metastatic disease and PFS in patients with RCC.
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Affiliation(s)
- Bruno R Tegel
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - Steffen Huber
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
| | - Lynn J Savic
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - MingDe Lin
- U/S Imaging and Interventions, Philips Research North America, Cambridge, MA, USA
| | - Bernhard Gebauer
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - Jeffrey Pollak
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
| | - Julius Chapiro
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
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12
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Differentiation of Clear Cell Renal Cell Carcinoma from other Renal Cell Carcinoma Subtypes and Benign Oncocytoma Using Quantitative MDCT Enhancement Parameters. ACTA ACUST UNITED AC 2020; 56:medicina56110569. [PMID: 33126571 PMCID: PMC7692100 DOI: 10.3390/medicina56110569] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Revised: 10/23/2020] [Accepted: 10/26/2020] [Indexed: 12/20/2022]
Abstract
Background and objectives: The use of non-invasive techniques to predict the histological type of renal masses can avoid a renal mass biopsy, thus being of great clinical interest. The aim of our study was to assess if quantitative multiphasic multidetector computed tomography (MDCT) enhancement patterns of renal masses (malignant and benign) may be useful to enable lesion differentiation by their enhancement characteristics. Materials and Methods: A total of 154 renal tumors were retrospectively analyzed with a four-phase MDCT protocol. We studied attenuation values using the values within the most avidly enhancing portion of the tumor (2D analysis) and within the whole tumor volume (3D analysis). A region of interest (ROI) was also placed in the adjacent uninvolved renal cortex to calculate the relative tumor enhancement ratio. Results: Significant differences were noted in enhancement and de-enhancement (diminution of attenuation measurements between the postcontrast phases) values by histology. The highest areas under the receiver operating characteristic curves (AUCs) of 0.976 (95% CI: 0.924–0.995) and 0.827 (95% CI: 0.752–0.887), respectively, were demonstrated between clear cell renal cell carcinoma (ccRCC) and papillary RCC (pRCC)/oncocytoma. The 3D analysis allowed the differentiation of ccRCC from chromophobe RCC (chrRCC) with a AUC of 0.643 (95% CI: 0.555–0.724). Wash-out values proved useful only for discrimination between ccRCC and oncocytoma (43.34 vs 64.10, p < 0.001). However, the relative tumor enhancement ratio (corticomedullary (CM) and nephrographic phases) proved useful for discrimination between ccRCC, pRCC, and chrRCC, with the values from the CM phase having higher AUCs of 0.973 (95% CI: 0.929–0.993) and 0.799 (95% CI: 0.721–0.864), respectively. Conclusions: Our observations point out that imaging features may contribute to providing prognostic information helpful in the management strategy of renal masses.
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13
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Association of tumor grade, enhancement on multiphasic CT and microvessel density in patients with clear cell renal cell carcinoma. Abdom Radiol (NY) 2020; 45:3184-3192. [PMID: 31650375 DOI: 10.1007/s00261-019-02271-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
PURPOSE Clear cell renal cell carcinoma (ccRCC) comprises nearly 90% of all diagnosed RCC subtypes and has the worst prognosis and highest metastatic potential. The strongest prognostic factors for patients with ccRCC include histological subtype and Fuhrman grade, which are incorporated into prognostic models. Since ccRCC is a highly vascularized tumor, there may be differences in enhancement patterns on multidetector CT (MDCT) due to the hemodynamics and microvessel density (MVD) of the lesions. This may provide a noninvasive method to characterize incidentally detected low- and high-grade ccRCCs on MDCT. The purpose of our study was to determine the correlation between MDCT enhancement parameters, ccRCC MVD, and Fuhrman grade to determine its utility and value in assessing tumor vascularity and grade in vivo. METHODS In this retrospective, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low-grade (LG), and 43 high-grade (HG) ccRCCs underwent preoperative four-phase MDCT. A 3D volume of interest (VOI) was obtained for every tumor and absolute enhancement and the wash-in/wash-out of enhancement for each phase was assessed. Immunohistochemistry on resected specimens was used to quantify MVD. Linear regression and Pearson correlation were used to investigate the strength of the association between 3D VOI enhancement and MVD. Stepwise logistic regression analysis determined independent predictors of HG ccRCC. Cut-off values and odds Ratio (OR) with 95% CIs were reported. The clinical, radiomic, and pathologic features with the highest performance in the stepwise logistic regression analysis were evaluated using receiver operator characteristics (ROC) and area under the curve (AUC). RESULTS Absolute enhancement in the nephrographic phase < 52.1 Hounsfield Units (HU) (HR 0.979, 95% CI 0.964-0.994, p value = 0.006), lesion size > 4.3 cm (HR 1.450, 95% CI 1.211-1.738, p value < 0.001), and an intratumoral MVD < 15% (HR 0.932, 95% CI 0.867-1.002, p value = 0.058) were independent predictors of HG ccRCC with an AUC of 0.818 (95% CI 0.725-0.911). HG ccRCCs had a significant association between 3D VOI enhancement and MVD in each post-contrast phase (r2 = 0.238 to 0.455, p < 0.05). CONCLUSIONS Absolute enhancement of the entire lesion obtained from a 3D VOI in the nephrographic phase on preoperative MDCT can provide quantitative data that are a significant, independent predictor of a high-grade clear cell RCC and can be used to assess tumor vascularity and grade in vivo.
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14
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Crispin-Ortuzar M, Gehrung M, Ursprung S, Gill AB, Warren AY, Beer L, Gallagher FA, Mitchell TJ, Mendichovszky IA, Priest AN, Stewart GD, Sala E, Markowetz F. Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform. JCO Clin Cancer Inform 2020; 4:736-748. [PMID: 32804543 PMCID: PMC7469624 DOI: 10.1200/cci.20.00026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/22/2020] [Indexed: 12/14/2022] Open
Abstract
PURPOSE Spatial heterogeneity of tumors is a major challenge in precision oncology. The relationship between molecular and imaging heterogeneity is still poorly understood because it relies on the accurate coregistration of medical images and tissue biopsies. Tumor molds can guide the localization of biopsies, but their creation is time consuming, technologically challenging, and difficult to interface with routine clinical practice. These hurdles have so far hindered the progress in the area of multiscale integration of tumor heterogeneity data. METHODS We have developed an open-source computational framework to automatically produce patient-specific 3-dimensional-printed molds that can be used in the clinical setting. Our approach achieves accurate coregistration of sampling location between tissue and imaging, and integrates seamlessly with clinical, imaging, and pathology workflows. RESULTS We applied our framework to patients with renal cancer undergoing radical nephrectomy. We created personalized molds for 6 patients, obtaining Dice similarity coefficients between imaging and tissue sections ranging from 0.86 to 0.96 for tumor regions and between 0.70 and 0.76 for healthy kidneys. The framework required minimal manual intervention, producing the final mold design in just minutes, while automatically taking into account clinical considerations such as a preference for specific cutting planes. CONCLUSION Our work provides a robust and automated interface between imaging and tissue samples, enabling the development of clinical studies to probe tumor heterogeneity on multiple spatial scales.
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Affiliation(s)
- Mireia Crispin-Ortuzar
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Marcel Gehrung
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Stephan Ursprung
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Andrew B. Gill
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Anne Y. Warren
- Department of Histopathology, Cambridge University Hospitals National Health Service (NHS) Foundation Trust, Cambridge, United Kingdom
| | - Lucian Beer
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | | | - Thomas J. Mitchell
- Department of Surgery, University of Cambridge, Cambridge, United Kingdom
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Iosif A. Mendichovszky
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Andrew N. Priest
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Grant D. Stewart
- Department of Surgery, University of Cambridge, Cambridge, United Kingdom
| | - Evis Sala
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Florian Markowetz
- Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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15
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Heller MT, Furlan A, Kawashima A. Multiparametric MR for Solid Renal Mass Characterization. Magn Reson Imaging Clin N Am 2020; 28:457-469. [PMID: 32624162 DOI: 10.1016/j.mric.2020.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Multiparametric MR provides a noninvasive means for improved differentiation between benign and malignant solid renal masses. Although most large, heterogeneous renal masses are due to renal cell carcinoma, smaller "indeterminate" renal masses are being identified on cross-sectional imaging. Although definitive diagnosis of a solid renal mass may not always be possible by MR imaging, integrated evaluation of multiple MR imaging parameters can result in concise differential diagnosis. Multiparametric MR should be considered a critical step in the triage of patients with a solid renal mass for whom treatment options are being considered in the context of morbidity, prognosis, and mortality.
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Affiliation(s)
- Matthew T Heller
- Department of Radiology, Mayo Clinic, Mayo Clinic Hospital, 5777 East Mayo Boulevard, PX SS 01 RADLGY, Phoenix, AZ 85054, USA.
| | - Alessandro Furlan
- Department of Radiology, University of Pittsburgh, University of Pittsburgh Medical Center, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Akira Kawashima
- Department of Radiology, Mayo Clinic, Mayo Clinic Hospital, 5777 East Mayo Boulevard, PX SS 01 RADLGY, Phoenix, AZ 85054, USA
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16
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Diagnostic test accuracy of ADC values for identification of clear cell renal cell carcinoma: systematic review and meta-analysis. Eur Radiol 2020; 30:4023-4038. [PMID: 32144458 DOI: 10.1007/s00330-020-06740-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/14/2020] [Accepted: 02/11/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVES To perform a systematic review on apparent diffusion coefficient (ADC) values of renal tumor subtypes and meta-analysis on the diagnostic performance of ADC for differentiation of localized clear cell renal cell carcinoma (ccRCC) from other renal tumor types. METHODS Medline, Embase, and the Cochrane Library databases were searched for studies published until May 1, 2019, that reported ADC values of renal tumors. Methodological quality was evaluated. For the meta-analysis on diagnostic test accuracy of ADC for differentiation of ccRCC from other renal lesions, we applied a bivariate random-effects model and compared two subgroups of ADC measurement with vs. without cystic and necrotic areas. RESULTS We included 48 studies (2588 lesions) in the systematic review and 13 studies (1126 lesions) in the meta-analysis. There was no significant difference in ADC of renal parenchyma using b values of 0-800 vs. 0-1000 (p = 0.08). ADC measured on selected portions (sADC) excluding cystic and necrotic areas differed significantly from whole-lesion ADC (wADC) (p = 0.002). Compared to ccRCC, minimal-fat angiomyolipoma, papillary RCC, and chromophobe RCC showed significantly lower sADC while oncocytoma exhibited higher sADC. Summary estimates of sensitivity and specificity to differentiate ccRCC from other tumors were 80% (95% CI, 0.76-0.88) and 78% (95% CI, 0.64-0.89), respectively, for sADC and 77% (95% CI, 0.59-0.90) and 77% (95% CI, 0.69-0.86) for wADC. sADC offered a higher area under the receiver operating characteristic curve than wADC (0.852 vs. 0.785, p = 0.02). CONCLUSIONS ADC values of kidney tumors that exclude cystic or necrotic areas more accurately differentiate ccRCC from other renal tumor types than whole-lesion ADC values. KEY POINTS • Selective ADC of renal tumors, excluding cystic and necrotic areas, provides better discriminatory ability than whole-lesion ADC to differentiate clear cell RCC from other renal lesions, with area under the receiver operating characteristic curve (AUC) of 0.852 vs. 0.785, respectively (p = 0.02). • Selective ADC of renal masses provides moderate sensitivity and specificity of 80% and 78%, respectively, for differentiation of clear cell renal cell carcinoma (RCC) from papillary RCC, chromophobe RCC, oncocytoma, and minimal-fat angiomyolipoma. • Selective ADC excluding cystic and necrotic areas are preferable to whole-lesion ADC as an additional tool to multiphasic MRI to differentiate clear cell RCC from other renal lesions whether the highest b value is 800 or 1000.
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17
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Feng Z, Lou S, Zhang L, Zhang L, Lan W, Wang M, Shen Q, Hu Z, Chen F. New Preoperative Nomogram Using the Centrality Index to Predict High Nuclear Grade Clear Cell Renal Carcinoma. Cancer Manag Res 2019; 11:10921-10928. [PMID: 32099456 PMCID: PMC6997223 DOI: 10.2147/cmar.s229571] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Accepted: 12/02/2019] [Indexed: 01/15/2023] Open
Abstract
Objective Nuclear grading is an independent prognosis factor of clear-cell renal cell carcinoma (ccRCC). A non-invasive preoperative predictive WHO/International Society of Urologic Pathology (WHO/ISUP) grading of ccRCC model is needed for clinical use. The anatomical complexity scoring system can span a variety of image modalities. The Centrality index (CI) is a quantitatively anatomical score commonly used for renal tumors. The purpose of this study was to develop a simple model to predict WHO/ISUP grading based on CI. Materials and methods The data in this study were from 248 ccRCC patients from five hospitals. We developed three predictive models using training data from 167 patients: a CI-only model, a valuable clinical parameter model and a fusion model of CI with valuable clinical parameters. We compared and evaluated the three models by discrimination, clinical usefulness and calibration, then tested them in a set of validation data from 81 patients. Results The fusion model consisting of CI and tumor size (valuable clinical parameter) had an area under the curve (AUC) of 0.82. In the validation set, the AUC was 0.85. The decision curve showed that the model had a good net benefit between the threshold probabilities of 5–80%. And the calibration curve showed good calibration in the training set and validation set. Conclusion This study confirms that CI is associated with the WHO/ISUP grade of ccRCC, and the possibility that a bivariate model incorporating tumor size may help urologist’s evaluation patients’ prognostic.
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Affiliation(s)
- Zhan Feng
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People's Republic of China
| | - Shuangshuang Lou
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People's Republic of China
| | - Lixia Zhang
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People's Republic of China
| | - Liang Zhang
- Department of Radiology, Zhejiang Cancer Hospital, Hangzhou 310003, People's Republic of China
| | - Wenting Lan
- Department of Radiology, Ningbo First Hospital, Ningbo 315000, People's Republic of China
| | - Minhong Wang
- Department of Radiology, Yijishan Hospital of Wannan Medical College, Wuhu 241000, People's Republic of China
| | - Qijun Shen
- Department of Radiology, Hangzhou First People's Hospital, Hangzhou 310003, People's Republic of China
| | - Zhengyu Hu
- Department of Radiology, Second People's Hospital of Yuhang District, Hangzhou 310003, People's Republic of China
| | - Feng Chen
- Department of Radiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, People's Republic of China
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18
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Zhang L, Zhou H, Gu D, Tian J, Zhang B, Dong D, Mo X, Liu J, Luo X, Pei S, Dong Y, Huang W, Chen Q, Liang C, Lian Z, Zhang S. Radiomic Nomogram: Pretreatment Evaluation of Local Recurrence in Nasopharyngeal Carcinoma based on MR Imaging. J Cancer 2019; 10:4217-4225. [PMID: 31413740 PMCID: PMC6691694 DOI: 10.7150/jca.33345] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Accepted: 05/25/2019] [Indexed: 12/12/2022] Open
Abstract
Background: To develop and validate a radiomic nomogram incorporating radiomic features with clinical variables for individual local recurrence risk assessment in nasopharyngeal carcinoma (NPC) patients before initial treatment. Methods: One hundred and forty patients were randomly divided into a training cohort (n = 80) and a validation cohort (n = 60). A total of 970 radiomic features were extracted from pretreatment magnetic resonance (MR) images of NPC patients from May 2007 to December 2013. Univariate and multivariate analyses were used for selecting radiomic features associated with local recurrence, and multivariate analyses was used for building radiomic nomogram. Results: Eight contrast-enhanced T1-weighted (CET1-w) image features and seven T2-weighted (T2-w) image features were selected to build a Cox proportional hazard model in the training cohort, respectively. The radiomic nomogram, which combined radiomic features and multiple clinical variables, had a good evaluation ability (C-index: 0.74 [95% CI: 0.58, 0.85]) in the validation cohort. The radiomic nomogram successfully categorized those patients into low- and high-risk groups with significant differences in the rate of local recurrence-free survival (P <0.05). Conclusions: This study demonstrates that MR imaging-based radiomics can be used as an aid tool for the evaluation of local recurrence, in order to develop tailored treatment targeting specific characteristics of individual patients.
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Affiliation(s)
- Lu Zhang
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Hongyu Zhou
- Institute of Automation, Chinese Academy of Sciences, CAS Key Laboratory of Molecular Imaging, Beijing, PR China
| | - Dongsheng Gu
- Institute of Automation, Chinese Academy of Sciences, CAS Key Laboratory of Molecular Imaging, Beijing, PR China
| | - Jie Tian
- Institute of Automation, Chinese Academy of Sciences, CAS Key Laboratory of Molecular Imaging, Beijing, PR China
| | - Bin Zhang
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, PR China.,Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, Guangdong, PR China
| | - Di Dong
- Institute of Automation, Chinese Academy of Sciences, CAS Key Laboratory of Molecular Imaging, Beijing, PR China
| | - Xiaokai Mo
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Jing Liu
- Affiliated Hospital of Guizhou Medical University, Guiyang, Department of Radiology Guiyang, Guizhou, PR China
| | - Xiaoning Luo
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Shufang Pei
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Yuhao Dong
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Wenhui Huang
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Qiuyin Chen
- Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, PR China.,Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, Guangdong, PR China
| | - Changhong Liang
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Zhouyang Lian
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
| | - Shuixing Zhang
- Department of Radiology, Guangdong Provincial People's Hospital/ Guangdong Academy of Medical Sciences, Guangzhou, Guangdong, PR China
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19
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Abstract
Renal tumors encompass a heterogeneous disease spectrum, which confounds patient management and treatment. Percutaneous biopsy is limited by an inability to sample every part of the tumor. Radiomics may provide detail beyond what can be achieved from human interpretation. Understanding what new technologies offer will allow radiologists to play a greater role in caring for patients with renal cell carcinoma. In this article, we review the use of radiomics in renal cell carcinoma, in both the pretreatment assessment of renal masses and posttreatment evaluation of renal cell carcinoma, with special emphasis on the use of multiparametric MR imaging datasets.
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Coy H, Young JR, Douek ML, Pantuck A, Brown MS, Sayre J, Raman SS. Association of qualitative and quantitative imaging features on multiphasic multidetector CT with tumor grade in clear cell renal cell carcinoma. Abdom Radiol (NY) 2019; 44:180-189. [PMID: 29987358 DOI: 10.1007/s00261-018-1688-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
PURPOSE The purpose of the study was to determine if enhancement features and qualitative imaging features on multiphasic multidetector computed tomography (MDCT) were associated with tumor grade in patients with clear cell renal cell carcinoma (ccRCC). METHODS In this retrospective, IRB approved, HIPAA-compliant, institutional review board-approved study with waiver of informed consent, 127 consecutive patients with 89 low grade (LG) and 43 high grade (HG) ccRCCs underwent preoperative four-phase MDCT in unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases. Previously published quantitative (absolute peak lesion enhancement, absolute peak lesion enhancement relative to normal enhancing renal cortex, 3D whole lesion enhancement and the wash-in/wash-out of enhancement within the 3D whole lesion ROI) and qualitative (enhancement pattern; presence of necrosis; pattern of; tumor margin; tumor-parenchymal interface, tumor-parenchymal interaction; intratumoral vascularity; collecting system infiltration; renal vein invasion; and calcification) assessments were obtained for each lesion independently by two fellowship-trained genitourinary radiologists. Comparisons between variables included χ2, ANOVA, and student t test. p values less than 0.05 were considered to be significant. Inter-reader agreement was obtained with the Gwet agreement coefficient (AC1) and standard error (SE) was reported. RESULTS No significant differences were observed between the LG and HG ccRCC cohorts with respect to absolute peak lesion enhancement and relative lesion enhancement ratio. There was a significant inverse correlation between low and high grade ccRCC and tumor enhancement the NP (71 HU vs. 54 HU, p < 0.001) and EX (52 HU vs. 39 HU, p < 0.001) phases using the 3D whole lesion ROI method. The percent wash-in of 3D enhancement from the UN to the CM phase was also significantly different between LG and HG ccRCCs (352% vs. 255%, p = 0.003). HG lesions showed significantly more calcification, necrosis, collecting system infiltration and ill-defined tumor margins (p < 0.05). Overall agreement between the two readers had a mean AC1 of 0.8172 (SE 0.0235). CONCLUSIONS Quantitatively, high grade ccRCC had significantly lower whole lesion enhancement in the NP and EX phases on MDCT. Qualitatively, high grade ccRCC were significantly more likely to be associated with calcifications, necrosis, collecting system infiltration, and an ill-defined tumor margin.
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Affiliation(s)
- Heidi Coy
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, 924 Westwood Boulevard, Suite 650, Los Angeles, CA, 90024, USA.
| | - Jonathan R Young
- Department of Radiology, University of California, Davis, 4860 Y Street, Suite 3100, Sacramento, CA, 95817, USA
| | - Michael L Douek
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, 924 Westwood Boulevard, Suite 650, Los Angeles, CA, 90024, USA
| | - Alan Pantuck
- Department of Urology, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, Clark Urology Center-Westwood, 200 Medical Plaza, Suite 140, Los Angeles, CA, 90095, USA
| | - Matthew S Brown
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Ronald Reagan-UCLA Medical Center, 924 Westwood Boulevard, Suite 650, Los Angeles, CA, 90024, USA
| | - James Sayre
- Department of Biostatistics, UCLA School of Public Heath, Room 51-253A, Los Angeles, CA, 90095, USA
| | - Steven S Raman
- UCLA Department of Radiological Sciences, Ronald Reagan UCLA Medical Center, 757 Westwood Plaza, RRUMC 1621H, Box 957437, Los Angeles, CA, 90095, USA
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21
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Zhou JY, Wang YC, Zeng CH, Ju SH. Renal Functional MRI and Its Application. J Magn Reson Imaging 2018; 48:863-881. [PMID: 30102436 DOI: 10.1002/jmri.26180] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 04/10/2018] [Indexed: 12/11/2022] Open
Abstract
Renal function varies according to the nature and stage of diseases. Renal functional magnetic resonance imaging (fMRI), a technique considered superior to the most common method used to estimate the glomerular filtration rate, allows for noninvasive, accurate measurements of renal structures and functions in both animals and humans. It has become increasingly prevalent in research and clinical applications. In recent years, renal fMRI has developed rapidly with progress in MRI hardware and emerging postprocessing algorithms. Function-related imaging markers can be acquired via renal fMRI, encompassing water molecular diffusion, perfusion, and oxygenation. This review focuses on the progression and challenges of the main renal fMRI methods, including dynamic contrast-enhanced MRI, blood oxygen level-dependent MRI, diffusion-weighted imaging, diffusion tensor imaging, arterial spin labeling, fat fraction imaging, and their recent clinical applications. LEVEL OF EVIDENCE 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:863-881.
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Affiliation(s)
- Jia-Ying Zhou
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Yuan-Cheng Wang
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Chu-Hui Zeng
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
| | - Sheng-Hong Ju
- Jiangsu Key Laboratory of Molecular and Functional Imaging, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
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22
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Abstract
Recent improvements in arterial spin labeled (ASL) and vastly undersampled dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) acquisitions are providing a new opportunity to explore the routine use of quantitative perfusion imaging for evaluation of a variety of abdominal diseases in clinical practice. In this review, we discuss different approaches for the acquisition and data analysis of ASL and DCE MRI techniques for quantification of tissue perfusion and present various clinical applications of these techniques in both neoplastic and non-neoplastic conditions in the abdomen.
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Luna A, Martín Noguerol T, Mata LA. Bases de la imagen funcional II: técnicas emergentes de resonancia magnética y nuevos métodos de análisis. RADIOLOGIA 2018. [DOI: 10.1016/j.rx.2018.03.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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López JI, Angulo JC. Pathological Bases and Clinical Impact of Intratumor Heterogeneity in Clear Cell Renal Cell Carcinoma. Curr Urol Rep 2018; 19:3. [PMID: 29374850 DOI: 10.1007/s11934-018-0754-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Intratumor heterogeneity is an inherent event in tumor development that is receiving much attention in the last years since it is responsible for most failures of current targeted therapies. The purpose of this review is to offer clinicians an updated insight of the multiple manifestations of a complex event that impacts significantly patient's life. RECENT FINDINGS Clear cell renal cell carcinoma is the most common renal tumor and a paradigmatic example of a heterogeneous neoplasm. Next-generation sequencing has demonstrated that intratumor heterogeneity encompasses genetic, epigenetic, and microenvironmental variability. Currently accepted protocols of tumor sampling seem insufficient in unveiling intratumor heterogeneity with reliability and need to be updated. This variability challenges the precise morphological diagnosis, its molecular characterization, and the selection of optimal personalized therapies in clear cell renal cell carcinoma, a neoplasm traditionally considered chemo- and radio-resistant. We review the state of the art of the different approaches to intratumor heterogeneity in clear cell renal cell carcinomas, from the simple morphology to the most sophisticated massive sequencing tools.
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Affiliation(s)
- José I López
- Department of Pathology, Cruces University Hospital, Biocruces Research Institute, University of the Basque Country (UPV/EHU), 48903, Barakaldo, Spain.
| | - Javier C Angulo
- Clinical Department, Urology, Hospital Universitario de Getafe, Universidad Europea de Madrid, 28905, Madrid, Spain
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Non-Invasive Renal Perfusion Imaging Using Arterial Spin Labeling MRI: Challenges and Opportunities. Diagnostics (Basel) 2018; 8:diagnostics8010002. [PMID: 29303965 PMCID: PMC5871985 DOI: 10.3390/diagnostics8010002] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 12/25/2017] [Accepted: 01/02/2018] [Indexed: 12/28/2022] Open
Abstract
Tissue perfusion allows for delivery of oxygen and nutrients to tissues, and in the kidneys is also a key determinant of glomerular filtration. Quantification of regional renal perfusion provides a potential window into renal (patho) physiology. However, non-invasive, practical, and robust methods to measure renal perfusion remain elusive, particularly in the clinic. Arterial spin labeling (ASL), a magnetic resonance imaging (MRI) technique, is arguably the only available method with potential to meet all these needs. Recent developments suggest its viability for clinical application. This review addresses several of these developments and discusses remaining challenges with the emphasis on renal imaging in human subjects.
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Development of a Patient-specific Tumor Mold Using Magnetic Resonance Imaging and 3-Dimensional Printing Technology for Targeted Tissue Procurement and Radiomics Analysis of Renal Masses. Urology 2017; 112:209-214. [PMID: 29056576 DOI: 10.1016/j.urology.2017.08.056] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 05/19/2017] [Accepted: 08/31/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To implement a platform for colocalization of in vivo quantitative multiparametric magnetic resonance imaging features with ex vivo surgical specimens of patients with renal masses using patient-specific 3-dimensional (3D)-printed tumor molds, which may aid in targeted tissue procurement and radiomics and radiogenomic analyses. MATERIALS AND METHODS Volumetric segmentation of 6 renal masses was performed with 3D Slicer (http://www.slicer.org) to create a 3D tumor model. A slicing guide template was created with specialized software, which included notches corresponding to the anatomic locations of the magnetic resonance images. The tumor model was subtracted from the slicing guide to create a depression in the slicing guide corresponding to the exact size and shape of the tumor. A customized, tumor-specific, slicing guide was then printed using a 3D printer. After partial nephrectomy, the surgical specimen was bivalved through the preselected magnetic resonance imaging (MRI) plane. A thick slab of the tumor was obtained, fixed, and processed as a whole-mount slide and was correlated to multiparametric MRI findings. RESULTS All patients successfully underwent partial nephrectomy and adequate fitting of the tumor specimens within the 3D mold was achieved in all tumors. Distinct in vivo MRI features corresponded to unique pathologic characteristics in the same tumor. The average cost of printing each mold was US$160.7 ± 111.1 (range: US$20.9-$350.7). CONCLUSION MRI-based preoperative 3D printing of tumor-specific molds allow for accurate sectioning of the tumor after surgical resection and colocalization of in vivo imaging features with tissue-based analysis in radiomics and radiogenomic studies.
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PET-MRI of the Pancreas and Kidneys. CURRENT RADIOLOGY REPORTS 2017. [DOI: 10.1007/s40134-017-0229-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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28
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Xi Y, Yuan Q, Zhang Y, Madhuranthakam AJ, Fulkerson M, Margulis V, Brugarolas J, Kapur P, Cadeddu JA, Pedrosa I. Statistical clustering of parametric maps from dynamic contrast enhanced MRI and an associated decision tree model for non-invasive tumour grading of T1b solid clear cell renal cell carcinoma. Eur Radiol 2017; 28:124-132. [PMID: 28681074 DOI: 10.1007/s00330-017-4925-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2017] [Revised: 04/27/2017] [Accepted: 06/05/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVES To apply a statistical clustering algorithm to combine information from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) into a single tumour map to distinguish high-grade from low-grade T1b clear cell renal cell carcinoma (ccRCC). METHODS This prospective, Institutional Review Board -approved, Health Insurance Portability and Accountability Act -compliant study included 18 patients with solid T1b ccRCC who underwent pre-surgical DCE MRI. After statistical clustering of the parametric maps of the transfer constant between the intravascular and extravascular space (K trans ), rate constant (K ep ) and initial area under the concentration curve (iAUC) with a fuzzy c-means (FCM) algorithm, each tumour was segmented into three regions (low/medium/high active areas). Percentages of each region and tumour size were compared to tumour grade at histopathology. A decision-tree model was constructed to select the best parameter(s) to predict high-grade ccRCC. RESULTS Seven high-grade and 11 low-grade T1b ccRCCs were included. High-grade histology was associated with higher percent high active areas (p = 0.0154) and this was the only feature selected by the decision tree model, which had a diagnostic performance of 78% accuracy, 86% sensitivity, 73% specificity, 67% positive predictive value and 89% negative predictive value. CONCLUSIONS The FCM integrates multiple DCE-derived parameter maps and identifies tumour regions with unique pharmacokinetic characteristics. Using this approach, a decision tree model using criteria beyond size to predict tumour grade in T1b ccRCCs is proposed. KEY POINTS • Tumour size did not correlate with tumour grade in T1b ccRCC. • Tumour heterogeneity can be analysed using statistical clustering via DCE-MRI parameters. • High-grade ccRCC has a larger percentage of high active area than low-grade ccRCCs. • A decision-tree model offers a simple way to differentiate high/low-grade ccRCCs.
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Affiliation(s)
- Yin Xi
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Qing Yuan
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Yue Zhang
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Ananth J Madhuranthakam
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA.,Advanced Imaging Research Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Michael Fulkerson
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA
| | - Vitaly Margulis
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - James Brugarolas
- Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Department of Internal Medicine, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Payal Kapur
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Department of Pathology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, Texas, USA
| | - Jeffrey A Cadeddu
- Department of Urology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, 75235-9085, USA. .,Advanced Imaging Research Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA. .,Kidney Cancer Program, Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, 2201 Inwood Road, Dallas, TX, USA.
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29
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Becker AS, Rossi C. Renal Arterial Spin Labeling Magnetic Resonance Imaging. Nephron Clin Pract 2016; 135:1-5. [PMID: 27760424 DOI: 10.1159/000450797] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 09/06/2016] [Indexed: 12/13/2022] Open
Abstract
Arterial spin labeling (ASL) MRI allows the quantification of tissue perfusion without administration of exogenous contrast agents. Patients with reduced renal function or other contraindications to Gadolinium-based contrast media may benefit from the non-invasive monitoring of tissue microcirculation. So far, only few studies have investigated the sensitivity, the specificity and the reliability of the ASL techniques for the assessment of renal perfusion. Moreover, only little is known about the interplay between ASL markers of perfusion and functional renal filtration parameters. In this editorial, we discuss the main technical issues related to the quantification of renal perfusion by ASL and, in particular, the latest results in patients with kidney disorders.
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Affiliation(s)
- Anton S Becker
- Department of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
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