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Li ZM, Zhou W, Feng L, Zhang HY, Chen WB. Predictive value of preoperative CT enhancement rate and CT perfusion parameters in colorectal cancer. BMC Gastroenterol 2024; 24:176. [PMID: 38773485 PMCID: PMC11106990 DOI: 10.1186/s12876-024-03257-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 05/07/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Angiogenesis is a critical step in colorectal cancer growth, progression and metastasization. CT are routine imaging examinations for preoperative clinical evaluation in colorectal cancer patients. This study aimed to investigate the predictive value of preoperative CT enhancement rate (CER) and CT perfusion parameters on angiogenesis in colorectal cancer, as well as the association of preoperative CER and CT perfusion parameters with serum markers. METHODS This retrospective analysis included 42 patients with colorectal adenocarcinoma. Median of microvessel density (MVD) as the cut-off value, it divided 42 patients into high-density group (MVD ≥ 35/field, n = 24) and low-density group (MVD < 35/field, n = 18), and 25 patients with benign colorectal lesions were collected as the control group. Statistical analysis of CER, CT perfusion parameters, serum markers were performed in all groups. Receiver operating curves (ROC) were plotted to evaluate the diagnostic efficacy of relevant CT perfusion parameters for tumor angiogenesis; Pearson correlation analysis explored potential association between CER, CT perfusion parameters and serum markers. RESULTS CER, blood volume (BV), blood flow (BF), permeability surface (PS) and carbohydrate antigen 19 - 9 (CA19-9), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), trefoil factor 3 (TFF3), vascular endothelial growth factor (VEGF) in colorectal adenocarcinoma were significantly higher than those in the control group, the parameters in high-density group were significantly higher than those in the low-density group (P < 0.05); however, the time to peak (TTP) of patients in colorectal adenocarcinoma were significantly lower than those in the control group, and the high-density group showed a significantly lower level compared to the low-density group (P < 0.05). The combined parameters BF + TTP + PS and BV + BF + TTP + PS demonstrated the highest area under the curve (AUC), both at 0.991. Pearson correlation analysis showed that the serum levels of CA19-9, CA125, CEA, TFF3, and VEGF in patients showed positive correlations with CER, BV, BF, and PS (P < 0.05), while these indicators exhibited negative correlations with TTP (P < 0.05). CONCLUSIONS Some single and joint preoperative CT perfusion parameters can accurately predict tumor angiogenesis in colorectal adenocarcinoma. Preoperative CER and CT perfusion parameters have certain association with serum markers.
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Affiliation(s)
- Ze-Mao Li
- North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, 063000, China
- North China University of Science and Technology, Tangshan, Hebei, 063000, China
| | - Wei Zhou
- North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, 063000, China
| | - Li Feng
- North China University of Science and Technology, Tangshan, Hebei, 063000, China
| | - Hui-Ying Zhang
- North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, 063000, China
| | - Wei-Bin Chen
- North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, 063000, China.
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Zheng HD, Huang QY, Huang QM, Ke XT, Ye K, Lin S, Xu JH. T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma. World J Gastrointest Oncol 2024; 16:819-832. [PMID: 38577440 PMCID: PMC10989374 DOI: 10.4251/wjgo.v16.i3.819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/30/2023] [Accepted: 01/29/2024] [Indexed: 03/12/2024] Open
Abstract
BACKGROUND The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.
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Affiliation(s)
- Hui-Da Zheng
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
| | - Qiao-Yi Huang
- Department of Gynaecology and Obstetrics, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
| | - Qi-Ming Huang
- Department of Computed Tomography/Magnetic Resonance Imaging, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
| | - Xiao-Ting Ke
- Department of Computed Tomography/Magnetic Resonance Imaging, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
| | - Kai Ye
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
| | - Shu Lin
- Centre of Neurological and Metabolic Research, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
- Group of Neuroendocrinology, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia
| | - Jian-Hua Xu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
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Dou Y, Liu Y, Kong X, Yang S. T staging with functional and radiomics parameters of computed tomography in colorectal cancer patients. Medicine (Baltimore) 2022; 101:e29244. [PMID: 35623068 PMCID: PMC9276127 DOI: 10.1097/md.0000000000029244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Accepted: 04/20/2022] [Indexed: 01/04/2023] Open
Abstract
Preoperative T staging is closely related to operation planning and prognosis of colorectal cancer (CRC). This study aimed to re-investigate the value of computed tomography (CT) in T stage evaluation of CRC patients with both functional and radiomics parameters.The functional and radiomics parameters of CT images and the clinical information were collected from 32 CRC patients. The radiomics parameters were measured based on manually labelled 5-mm circles using software Syngo. The radiomics parameters were computed based on labelled tumor regions using Python software package.A total of 125 parameters were collected and analyzed by using decision tree analysis. The decision tree analysis identified 6 rules. Based on the rules, the shape elongation, flow extraction of nodule and blood volume of tumor region were found to be of significance and could define a high-risk group and a low-risk group.This study shows the combination of functional parameters and radiomics parameters of CT is helpful for the diagnosis and T staging of CRC.
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Affiliation(s)
- Yafang Dou
- Department of Radiology, Shuguang Hospital of Shanghai Traditional Chinese Medicine University, Shanghai, China
| | - Yingying Liu
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Xiancheng Kong
- Department of General Surgery, Shuguang Hospital of Shanghai Traditional Chinese Medicine University, Shanghai, China
| | - Shangying Yang
- Department of Gastroscope, Shuguang Hospital of Shanghai Traditional Chinese Medicine University, Shanghai, China
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Garbino N, Brancato V, Salvatore M, Cavaliere C. A Systematic Review on the Role of the Perfusion Computed Tomography in Abdominal Cancer. Dose Response 2021; 19:15593258211056199. [PMID: 34880716 PMCID: PMC8647276 DOI: 10.1177/15593258211056199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 11/17/2022] Open
Abstract
Background and purpose Perfusion Computed Tomography (CTp) is an imaging technique which allows
quantitative and qualitative evaluation of tissue perfusion through dynamic
CT acquisitions. Since CTp is still considered a research tool in the field
of abdominal imaging, the aim of this work is to provide a systematic
summary of the current literature on CTp in the abdominal region to clarify
the role of this technique for abdominal cancer applications. Materials and Methods A systematic literature search of PubMed, Web of Science, and Scopus was
performed to identify original articles involving the use of CTp for
clinical applications in abdominal cancer since 2011. Studies were included
if they reported original data on CTp and investigated the clinical
applications of CTp in abdominal cancer. Results Fifty-seven studies were finally included in the study. Most of the included
articles (33/57) dealt with CTp at the level of the liver, while a low
number of studies investigated CTp for oncologic diseases involving UGI
tract (8/57), pancreas (8/57), kidneys (3/57), and colon–rectum (5/57). Conclusions Our study revealed that CTp could be a valuable functional imaging tool in
the field of abdominal oncology, particularly as a biomarker for monitoring
the response to anti-tumoral treatment.
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Chen SH, Miles K, Taylor SA, Ganeshan B, Rodriquez M, Fraioli F, Wan S, Afaq A, Shortman R, Walls D, Hoy L, Endozo R, Bhargava A, Hanson M, Huang J, Raouf S, Francis D, Siddiqi S, Arulampalam T, Sizer B, Machesney M, Reay-Jones N, Dindyal S, Ng T, Groves AM. FDG-PET/CT in colorectal cancer: potential for vascular-metabolic imaging to provide markers of prognosis. Eur J Nucl Med Mol Imaging 2021; 49:371-384. [PMID: 33837843 PMCID: PMC8712298 DOI: 10.1007/s00259-021-05318-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/13/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE This study assesses the potential for vascular-metabolic imaging with FluoroDeoxyGlucose (FDG)-Positron Emission Tomography/Computed Tomography (PET/CT) perfusion to provide markers of prognosis specific to the site and stage of colorectal cancer. METHODS This prospective observational study comprised of participants with suspected colorectal cancer categorized as either (a) non-metastatic colon cancer (M0colon), (b) non-metastatic rectal cancer (M0rectum), or (c) metastatic colorectal cancer (M+). Combined FDG-PET/CT perfusion imaging was successfully performed in 286 participants (184 males, 102 females, age: 69.60 ± 10 years) deriving vascular and metabolic imaging parameters. Vascular and metabolic imaging parameters alone and in combination were investigated with respect to overall survival. RESULTS A vascular-metabolic signature that was significantly associated with poorer survival was identified for each patient group: M0colon - high Total Lesion Glycolysis (TLG) with increased Permeability Surface Area Product/Blood Flow (PS/BF), Hazard Ratio (HR) 3.472 (95% CI: 1.441-8.333), p = 0.006; M0rectum - high Metabolic Tumour Volume (MTV) with increased PS/BF, HR 4.567 (95% CI: 1.901-10.970), p = 0.001; M+ participants, high MTV with longer Time To Peak (TTP) enhancement, HR 2.421 (95% CI: 1.162-5.045), p = 0.018. In participants with stage 2 colon cancer as well as those with stage 3 rectal cancer, the vascular-metabolic signature could stratify the prognosis of these participants. CONCLUSION Vascular and metabolic imaging using FDG-PET/CT can be used to synergise prognostic markers. The hazard ratios suggest that the technique may have clinical utility.
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Affiliation(s)
- Shih-hsin Chen
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
- Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Kenneth Miles
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
| | - Stuart A. Taylor
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
- Centre for Medical Imaging, University College London, London, UK
| | - Balaji Ganeshan
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
| | - Manuel Rodriquez
- University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
- Department of Research Pathology, Cancer Institute, UCL, London, UK
| | - Francesco Fraioli
- University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
| | - Simon Wan
- University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
| | - Asim Afaq
- University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
- University of Iowa, Carver College of Medicine, Iowa City, USA
| | - Robert Shortman
- Department of Nuclear Medicine, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Darren Walls
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
| | - Luke Hoy
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
| | - Raymond Endozo
- University College London Hospitals (UCLH) NHS Foundation Trust, Surgery and Cancer Board, Imaging Division, University College Hospital (UCH), London, UK
| | - Aman Bhargava
- Institute of Health Barts and London Medical School, Queen Mary University of London (QMUL), London, UK
| | - Matthew Hanson
- Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK
| | - Joseph Huang
- Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK
| | - Sherif Raouf
- Barking, Havering and Redbridge University Hospitals NHS Trust, Division of Cancer and Clinical Support, Queens and King George Hospitals, Essex, UK
- Radiotherapy Department, Barts Cancer Centre, St Bartholomew’s Hospital, West Smithfield, London, UK
| | - Daren Francis
- Royal Free London NHS Foundation Trust, Department of Colorectal Surgery, Barnet and Chase Farm Hospitals, London, UK
| | - Shahab Siddiqi
- Mid Essex Hospital Services NHS Trust, Department of Lower GI Surgery and Coloproctology, Broomfield Hospital, Essex, UK
| | - Tan Arulampalam
- East Suffolk and North Essex NHS Foundation Trust, Department of Surgery & Department of Clinical Oncology, Colchester General Hospital, Essex, UK
| | - Bruce Sizer
- East Suffolk and North Essex NHS Foundation Trust, Department of Surgery & Department of Clinical Oncology, Colchester General Hospital, Essex, UK
| | - Michael Machesney
- Barts Health NHS Trust, Cancer Clinical Board, Colorectal Surgery, Whipps Cross Hospital, London, UK
| | - Nicholas Reay-Jones
- East and North Hertfordshire NHS Trust, Colorectal Surgery, Queen Elizabeth II Hospital, Hertfordshire, UK
| | - Sanjay Dindyal
- East and North Hertfordshire NHS Trust, Colorectal Surgery, Lister Hospital, Hertfordshire, UK
| | - Tony Ng
- School of Cancer & Pharmaceutical Sciences, Kings College London (KCL), London, UK
| | - Ashley M Groves
- Division of Medicine, Research Department of Imaging, University College London (UCL), London, UK
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Mainenti PP, Stanzione A, Guarino S, Romeo V, Ugga L, Romano F, Storto G, Maurea S, Brunetti A. Colorectal cancer: Parametric evaluation of morphological, functional and molecular tomographic imaging. World J Gastroenterol 2019; 25:5233-5256. [PMID: 31558870 PMCID: PMC6761241 DOI: 10.3748/wjg.v25.i35.5233] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 08/06/2019] [Accepted: 08/24/2019] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancer (CRC) represents one of the leading causes of tumor-related deaths worldwide. Among the various tools at physicians’ disposal for the diagnostic management of the disease, tomographic imaging (e.g., CT, MRI, and hybrid PET imaging) is considered essential. The qualitative and subjective evaluation of tomographic images is the main approach used to obtain valuable clinical information, although this strategy suffers from both intrinsic and operator-dependent limitations. More recently, advanced imaging techniques have been developed with the aim of overcoming these issues. Such techniques, such as diffusion-weighted MRI and perfusion imaging, were designed for the “in vivo” evaluation of specific biological tissue features in order to describe them in terms of quantitative parameters, which could answer questions difficult to address with conventional imaging alone (e.g., questions related to tissue characterization and prognosis). Furthermore, it has been observed that a large amount of numerical and statistical information is buried inside tomographic images, resulting in their invisibility during conventional assessment. This information can be extracted and represented in terms of quantitative parameters through different processes (e.g., texture analysis). Numerous researchers have focused their work on the significance of these quantitative imaging parameters for the management of CRC patients. In this review, we aimed to focus on evidence reported in the academic literature regarding the application of parametric imaging to the diagnosis, staging and prognosis of CRC while discussing future perspectives and present limitations. While the transition from purely anatomical to quantitative tomographic imaging appears achievable for CRC diagnostics, some essential milestones, such as scanning and analysis standardization and the definition of robust cut-off values, must be achieved before quantitative tomographic imaging can be incorporated into daily clinical practice.
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Affiliation(s)
- Pier Paolo Mainenti
- Institute of Biostructures and Bioimaging of the National Council of Research (CNR), Naples 80145, Italy
| | - Arnaldo Stanzione
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Salvatore Guarino
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Valeria Romeo
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Lorenzo Ugga
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Federica Romano
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Giovanni Storto
- IRCCS-CROB, Referral Cancer Center of Basilicata, Rionero in Vulture 85028, Italy
| | - Simone Maurea
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
| | - Arturo Brunetti
- University of Naples "Federico II", Department of Advanced Biomedical Sciences, Naples 80131, Italy
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García-Figueiras R, Baleato-González S, Padhani AR, Luna-Alcalá A, Marhuenda A, Vilanova JC, Osorio-Vázquez I, Martínez-de-Alegría A, Gómez-Caamaño A. Advanced Imaging Techniques in Evaluation of Colorectal Cancer. Radiographics 2018; 38:740-765. [PMID: 29676964 DOI: 10.1148/rg.2018170044] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Imaging techniques are clinical decision-making tools in the evaluation of patients with colorectal cancer (CRC). The aim of this article is to discuss the potential of recent advances in imaging for diagnosis, prognosis, therapy planning, and assessment of response to treatment of CRC. Recent developments and new clinical applications of conventional imaging techniques such as virtual colonoscopy, dual-energy spectral computed tomography, elastography, advanced computing techniques (including volumetric rendering techniques and machine learning), magnetic resonance (MR) imaging-based magnetization transfer, and new liver imaging techniques, which may offer additional clinical information in patients with CRC, are summarized. In addition, the clinical value of functional and molecular imaging techniques such as diffusion-weighted MR imaging, dynamic contrast material-enhanced imaging, blood oxygen level-dependent imaging, lymphography with contrast agents, positron emission tomography with different radiotracers, and MR spectroscopy is reviewed, and the advantages and disadvantages of these modalities are evaluated. Finally, the future role of imaging-based analysis of tumor heterogeneity and multiparametric imaging, the development of radiomics and radiogenomics, and future challenges for imaging of patients with CRC are discussed. Online supplemental material is available for this article. ©RSNA, 2018.
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Affiliation(s)
- Roberto García-Figueiras
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Sandra Baleato-González
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Anwar R Padhani
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Antonio Luna-Alcalá
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Ana Marhuenda
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Joan C Vilanova
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Iria Osorio-Vázquez
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Anxo Martínez-de-Alegría
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
| | - Antonio Gómez-Caamaño
- From the Departments of Radiology (R.G.F., S.B.G., I.O.V., A.M.d.A.) and Radiation Oncology (A.G.C.), Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706 Santiago de Compostela, Spain; Paul Strickland Scanner Centre, Mount Vernon Cancer Centre, Northwood, Middlesex, England (A.R.P.); Health Time, Jaén, Spain (A.L.A.); Department of Radiology, University Hospitals of Cleveland, Case Western Reserve University, Cleveland, Ohio (A.L.A.); Department of Radiology, IVO (Instituto Valenciano de Oncología), Valencia, Spain (A.M.); and Department of Radiology, Clínica Girona and IDI, Girona, Spain (J.C.V.)
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