Kenneth A Miles

Guy's and St Thomas' NHS Foundation Trust, Londinium, England, United Kingdom

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Publications (50)131.59 Total impact

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    ABSTRACT: Calcineurin inhibitors are substrates for P-glycoprotein (P-gp), the expression of which is associated with ABCB1 C3435T polymorphism. Individual P-gp response to calcineurin inhibitor may be linked to nephrotoxicity or rejection. Tc-2-Methoxyisobutylisonitrile (Tc-MIBI) is also a P-gp substrate. The aim of this study, therefore, was to determine Tc-MIBI organ kinetics and compare them with ABCB1 genotype with a view to replacing Tc-mercaptoacetyltriglycine (Tc-MAG3) with Tc-MIBI in renal transplant care.
    Nuclear Medicine Communications 07/2014; · 1.38 Impact Factor
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    ABSTRACT: Tumour heterogeneity has, in recent times, come to play a vital role in how we understand and treat cancers, however the clinical translation of this has lagged behind advances in research. Although significant advancements in oncological management have been made, personalised care remains an elusive goal. Inter and intra-tumour heterogeneity, particularly in the clinical setting, has been difficult to quantify and therefore to treat. The histological quantification of heterogeneity of tumours can be a logistical, and clinical challenge. The ability to not just examine the whole tumour but also all the molecular variations of metastatic disease in a patient is obviously difficult with current histological techniques. Advances in imaging techniques and novel applications, alongside our understanding of tumour heterogeneity have opened up a plethora of non-invasive biomarker potential to examine tumours, their heterogeneity and the clinical translation. This review will focus on how various imaging methods that allow for quantification of metastatic tumour heterogeneity, along with the potential of developing imaging, integrated with other in vitro diagnostics approaches such as genomics and exosome analyses, have the potential role as a non-invasive biomarker for guiding the treatment algorithm.
    The British journal of radiology 03/2014; · 2.11 Impact Factor
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    ABSTRACT: This study explores the potential for multifunctional imaging to provide a signature for V-KI-RAS2 Kirsten rat sarcoma viral oncogene homolog (KRAS) gene mutations in colorectal cancer. This prospective study approved by the institutional review board comprised 33 patients undergoing PET/CT before surgery for proven primary colorectal cancer. Tumor tissue was examined histologically for presence of the KRAS mutations and for expression of hypoxia-inducible factor-1 (HIF-1) and minichromosome maintenance protein 2 (mcm2). The following imaging parameters were derived for each tumor: (18)F-FDG uptake ((18)F-FDG maximum standardized uptake value [SUVmax]), CT texture (expressed as mean of positive pixels [MPP]), and blood flow measured by dynamic contrast-enhanced CT. A recursive decision tree was developed in which the imaging investigations were applied sequentially to identify tumors with KRAS mutations. Monte Carlo analysis provided mean values and 95% confidence intervals for sensitivity, specificity, and accuracy. The final decision tree comprised 4 decision nodes and 5 terminal nodes, 2 of which identified KRAS mutants. The true-positive rate, false-positive rate, and accuracy (95% confidence intervals) of the decision tree were 82.4% (63.9%-93.9%), 0% (0%-10.4%), and 90.1% (79.2%-96.0%), respectively. KRAS mutants with high (18)F-FDG SUVmax and low MPP showed greater frequency of HIF-1 expression (P = 0.032). KRAS mutants with low (18)F-FDG SUVmax, high MPP, and high blood flow expressed mcm2 (P = 0.036). Multifunctional imaging with PET/CT and recursive decision-tree analysis to combine measurements of tumor (18)F-FDG uptake, CT texture, and perfusion has the potential to identify imaging signatures for colorectal cancers with KRAS mutations exhibiting hypoxic or proliferative phenotypes.
    Journal of Nuclear Medicine 02/2014; · 5.77 Impact Factor
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    ABSTRACT: Non-invasive characterization of a tumor's molecular features could enhance treatment management. Quantitative computed tomography (CT) based texture analysis (QTA) has been used to derive tumor heterogeneity information, and the appearance of the tumors has been shown to relate to patient outcome in non-small cell lung cancer (NSCLC) and other cancers. In this study, we examined the potential of tumoral QTA to differentiate K-ras mutant from pan-wildtype tumors and its prognostic potential using baseline pre-treatment non-contrast CT imaging in NSCLC.
    PLoS ONE 01/2014; 9(7):e100244. · 3.53 Impact Factor
  • Computer Vision and Graphics, Edited by Chmielewski, LeszekJ. and Kozera, Ryszard and Shin, Bok-Suk and Wojciechowski, Konrad, 01/2014: pages 446-453; Springer International Publishing., ISBN: 9783319113302
  • Kenneth Miles
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    ABSTRACT: LEARNING OBJECTIVES 1) Describe the oncological imaging biomarkers available from CT. 2) Demonstrate knowledge of the processes required for qualification of CT biomarkers in oncological drug development and clinical practice. 3) Compare the applications of CT biomarkers for prognosis, response prediction and response assessment. ABSTRACT By measuring size and attenuation with or without contrast material, CT can provide a range of oncological biomarkers including T-stage, RECIST, enhancement, CT perfusion and CT texture analysis. Implementation of these biomarkers requires prior assessments of technical/biological performance and establishment of biomarker performance characteristics. For clinical applications, assessments of therapeutic and health impact are also required. Technical/biological validation includes assessments of test-retest performance and identification of relevant biological correlates. Evaluations of biomarker performance should report cross-validated diagnostic/prognostic thresholds, hazard ratio and biomarker prevalence. Based on these parameters, modelling studies can evaluate the potential therapeutic and health impacts that would result from clinical deployment. Current evidence supporting the use of CT biomarkers in drug development and clinical practice are summarised.
    Radiological Society of North America 2013 Scientific Assembly and Annual Meeting; 12/2013
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    ABSTRACT: PURPOSE To describe a decision modeling approach for the identification of potential clinical applications for prognostic imaging biomarkers in oncology. METHOD AND MATERIALS An approach that uses decision modeling to identify potential applications for prognostic imaging biomarkers was defined. The approach requires cross-validated data indicating the hazard ratio and proportion of high risk patients identified by the imaging biomarker along with the 95% confidence intervals (CI). The biomarker also needs to be prognostic independent of tumor stage and other potential imaging biomarkers. Decision modeling is then used to assess potential health outcomes and costs from proposed biomarker deployments with Monte Carlo analysis quantifying the likelihood of realizing beneficial outcomes. The approach was used to assess potential applications of CT texture analysis (CTTA) for the personalization of chemotherapy for patients with advanced non-small cell lung cancer. RESULTS The cross-validated mortality hazard ratio (95% confidence interval) for CTTA was 1.99 (1.14 – 3.44) with 52.5% (95% CI: 43.2 – 61.7%) categorized as high risk. Decision modeling identified CTTA-based strategies with high, intermediate and low likelihoods of clinical benefit and/or cost-effectiveness. Two strategies that used CTTA to identify sub-sets of patients with EGFR-negative tumors for 2-agent platinum based chemotherapy increased the survival benefit of this treatment to 5.3 months (95% CI:3.3 -7.3 months ) and were most likely to be cost-effective (Net monetary benefit $540; 95% CI: $369-702 and $762; 95% CI: $351-1154 respectively). CONCLUSION Decision modeling can be useful in the identification of potential clinical applications for prognostic imaging biomarkers in oncology. CLINICAL RELEVANCE/APPLICATION Methods that aid the identification of clinical applications for prognostic imaging biomarkers will promote their translation to personalized medicine.
    Radiological Society of North America 2013 Scientific Assembly and Annual Meeting; 12/2013
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    ABSTRACT: Fine-needle aspiration (FNA) has revolutionised the care of patients with thyroid nodules and is the initial investigation of choice. However, as a result of nondiagnostic (Thy1) and nonneoplastic (Thy2) specimens, it remains an imperfect sole solution with a range of sensitivities and a high inadequate ratio. Therefore the British Thyroid Association (BTA) guidelines recommend a second FNA immediately for Thy1 specimens and 3-6 months later for Thy2 specimens. Patients must be followed up to exclude malignancy. In this study we assessed the performance of MIBI scintigraphy for diagnosing thyroid malignancy and the cost-effectiveness of a combined FNA/MIBI investigative strategy for the management of thyroid nodules. The diagnostic performance of MIBI scintigraphy was calculated from a retrospective review of local data combined with a meta-analysis of the published literature. Decision tree analysis was used to calculate the cost-effectiveness of a combined FNA/MIBI investigative strategy compared to the BTA guidelines. From 712 patients, the sensitivity, specificity, PPV and NPV of MIBI scintigraphy for the diagnosis of malignancy were 96 %, 46 %, 34 % and 97 %, respectively. MIBI-based strategies were more accurate and associated with lower cost per patient (£1,855/ 2,125 vs. £2,445/ 2,801) and lower cost per cancer diagnosed (£1,902/ 2,179 vs. £2,469/ 2,828) with negligible change in life expectancy. Due to its high NPV, MIBI scintigraphy can usefully exclude malignancy for Thy1 and Thy2 lesions. Its low specificity means MIBI scintigraphy cannot be recommended as a first-line investigation, but as a second-line investigation MIBI scintigraphy may lead to a lower rate of unnecessary thyroidectomies. Combined FNA/MIBI strategies are potentially cost-effective in the management of solitary or dominant thyroid nodules.
    European Journal of Nuclear Medicine 09/2013; · 4.53 Impact Factor
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    ABSTRACT: Objective: Technetium-99m-labelled hexakis-methoxy-isobutyl isonitrile (Tc-99m-MIBI) is a substrate for P-glycoprotein (P-gp), an ATP-binding cassette (ABC) transporter protein, and can be used to image P-gp expression. The aim was to study normal kinetics of Tc-99m-MIBI in the kidney and liver to help understand physiological studies of P-gp expression in these organs. Methods: Thirty healthy kidney transplant donors received intravenous Tc-99m-MIBI followed by dynamic scintigraphy for 20 min and static imaging at 30 and 120 min. Time-activity curves were generated from parenchymal ROI. An assumed mono-exponential Tc-99m-MIBI blood clearance with rate constant of 0.3 min-1 was used to predict the Tc-99m-MIBI that would have accumulated in the organs had none left. The activities leaving were then calculated by subtraction and expressed as percentages of the predicted total accumulated activities. Results: Kidney time-activity curves peaked at 2-4 min then declined to a plateau from ~15min equal to 31 (SD 5)% of the total activity accumulated (corresponding to 69 [5]% rapidly eliminated) (phase 1). Bladder activity followed a similar but opposite time course. Between 30 and 120 min (phase 2), activity left at 0.36 (0.13) %.min-1. Liver curves peaked at 6-8 min. Differentiation of the elimination curve revealed that a variable proportion of tracer (5-56%; mean 30 [14]%) was rapidly excreted over ~11 min. From 30 min, activity left at 1.02 (0.23) %.min-1. There was no correlation between renal and hepatic elimination rates in either phase or between early and late phase elimination rates in either organ. Conclusions: Early renal elimination is predominantly via glomerular filtration and urinary excretion. The liver rapidly excretes a more variable and lower proportion of Tc-99m-MIBI than the kidney. P-gp located at the urine/tubule and bile/hepatocyte boundaries prevents Tc-99m-MIBI re-entering cells and thereby influences elimination and retention in both phases, although other ABC transporters are probably also involved.
    Drug metabolism letters. 06/2013;
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    Balaji Ganeshan, Kenneth A Miles
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    ABSTRACT: Heterogeneity is a key feature of malignancy associated with adverse tumour biology. Quantifying heterogeneity could provide a useful non-invasive imaging biomarker. Heterogeneity on computed tomography (CT) can be quantified using texture analysis which extracts spatial information from CT images (unenhanced, contrast-enhanced and derived images such as CT perfusion) that may not be perceptible to the naked eye. The main components of texture analysis can be categorized into image transformation and quantification. Image transformation filters the conventional image into its basic components (spatial, frequency, etc.) to produce derived subimages. Texture quantification techniques include structural-, model- (fractal dimensions), statistical- and frequency-based methods. The underlying tumour biology that CT texture analysis may reflect includes (but is not limited to) tumour hypoxia and angiogenesis. Emerging studies show that CT texture analysis has the potential to be a useful adjunct in clinical oncologic imaging, providing important information about tumour characterization, prognosis and treatment prediction and response.
    Cancer Imaging 01/2013; 13:140-9. · 1.59 Impact Factor
  • W Phillip Law, Kenneth A Miles
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    ABSTRACT: A prognostic imaging biomarker can be defined as an imaging characteristic that is objectively measurable and provides information on the likely outcome of the cancer disease in an untreated individual and should be distinguished from predictive imaging biomarkers and imaging markers of response. A range of tumour characteristics of potential prognostic value can be measured using a variety imaging modalities. However, none has currently been adopted into routine clinical practice. This article considers key examples of emerging prognostic imaging biomarkers and proposes an evaluation framework that aims to demonstrate clinical efficacy and so support their introduction into the clinical arena. With appropriate validation within an established evaluation framework, prognostic imaging biomarkers have the potential to contribute to individualized cancer care, in some cases reducing the financial burden of expensive cancer treatments by facilitating their more rational use.
    Cancer Imaging 01/2013; 13(3):332-41. · 1.59 Impact Factor
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    ABSTRACT: Analysis of texture within tumours on computed tomography (CT) is emerging as a potentially useful tool in assessing prognosis and treatment response for patients with cancer. This article illustrates the image and histological features that correlate with CT texture parameters obtained from tumours using the filtration-histogram approach, which comprises image filtration to highlight image features of a specified size followed by histogram analysis for quantification. Computer modelling can be used to generate texture parameters for a range of simple hypothetical images with specified image features. The model results are useful in explaining relationships between image features and texture parameters. The main image features that can be related to texture parameters are the number of objects highlighted by the filter, the brightness and/or contrast of highlighted objects relative to background attenuation, and the variability of brightness/contrast of highlighted objects. These relationships are also demonstrable by texture analysis of clinical CT images. The results of computer modelling may facilitate the interpretation of the reported associations between CT texture and histopathology in human tumours. The histogram parameters derived during the filtration-histogram method of CT texture analysis have specific relationships with a range of image features. Knowledge of these relationships can assist the understanding of results obtained from clinical CT texture analysis studies in oncology.
    Cancer Imaging 01/2013; 13(3):400-6. · 1.59 Impact Factor
  • Samuel D Kyle, W Phillip Law, Kenneth A Miles
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    ABSTRACT: Response prediction is an important emerging concept in oncologic imaging, with tailored, individualized treatment regimens increasingly becoming the standard of care. This review aims to define tumour response and illustrate the ways in which imaging techniques can demonstrate tumour biological characteristics that provide information on the likely benefit to be received by treatment. Two imaging approaches are described: identification of therapeutic targets and depiction of the treatment-resistant phenotype. The former approach is exemplified by the use of radionuclide imaging to confirm target expression before radionuclide therapy but with angiogenesis imaging and imaging correlates for genetic response predictors also demonstrating potential utility. Techniques to assess the treatment-resistant phenotype include demonstration of hypoperfusion with dynamic contrast-enhanced computed tomography and magnetic resonance imaging (MRI), depiction of necrosis with diffusion-weighted MRI, imaging of hypoxia and tumour adaption to hypoxia, and 99mTc-MIBI imaging of P-glycoprotein mediated drug resistance. To date, introduction of these techniques into clinical practice has often been constrained by inadequate cross-validation of predictive criteria and lack of verification against appropriate response end points such as survival. With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype. This ability to predict tumour response will have implications for improving efficacy of treatment, cost-effectiveness and omission of futile therapy.
    Cancer Imaging 01/2013; 13(3):381-90. · 1.59 Impact Factor
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    ABSTRACT: PURPOSE Heterogeneity is an important determinant of the tumor microenvironment that can be assessed by CT Texture Analysis (CTTA) incorporated into Positron Emission Tomography (PET) with 18F-fluorodeoxyglucose (FDG). This study investigates the relationship between tumor heterogeneity and FDG uptake in colorectal cancer. METHOD AND MATERIALS Sixty colorectal cancer patients were prospectively recruited. FDG-PET/CT imaging data undertaken for staging before primary tumor resection was analysed. Histological data on KRAS mutation status was available in 33 patients. The maximum standardized uptake value (SUVmax) for the primary tumor was calculated from FDG accumulation. CTTA used Laplacian of Gaussian filtration to assess tumor heterogeneity at fine, medium and coarse scales with quantification as standard-deviation (SD), skewness and kurtosis. SUVmax and CTTA parameters were compared between KRAS mutated (n= 17) and wild-type (n=16) groups. RESULTS SUVmax could not reliably distinguish the KRAS-mutated and wild-type groups (medians: 19.1 versus 14.6, p = 0.31). However, combined FDG-PET/CTTA showed that increased SUVmax of >=14 with low heterogeneity identified patients KRAS mutations with 73% accuracy. Sensitivity/specificity and p-values respectively for SD (fine), Skewness (medium), kurtosis (coarse): 65%/81%, 0.013; 71%/75%, 0.015; 76%/69%, 0.015. CONCLUSION This study indicates that high FDG accumulation with low tumor heterogeneity may be an imaging correlate for the KRAS mutation in colorectal cancer. Combined FDG-PET/CTTA has the potential to identify colorectal cancer patients with KRAS mutations. CLINICAL RELEVANCE/APPLICATION Imaging identification of the KRAS mutation may be of prognostic significance and impact on selection of neo-adjuvant chemotherapy.
    Radiological Society of North America 2012 Scientific Assembly and Annual Meeting; 11/2012
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    ABSTRACT: Purpose:To correlate computed tomographic (CT) texture in non-small cell lung cancer (NSCLC) with histopathologic markers for angiogenesis and hypoxia.Materials and Methods:The study was institutional review board approved, and informed consent was obtained. Fourteen patients with NSCLC underwent CT prior to intravenous administration of pimonidazole (0.5 g/m(2)), a marker of hypoxia, 24 hours before surgery. Texture was assessed for unenhanced and contrast material-enhanced CT images by using a software algorithm that selectively filters and extracts texture at different anatomic scales (1.0 [fine detail] to 2.5 [coarse features]), with quantification of the standard deviation (SD) of all pixel values and the mean value of positive pixels (MPP) and uniformity of distribution of positive gray-level pixel values (UPP). After surgery, matched tumor sections were stained for angiogenesis (CD34 expression) and for markers of hypoxia (glucose transporter protein 1 [Glut-1] and pimonidazole). The percentage and average intensity of the tumor stained were assessed. A linear mixed-effects model was used to assess the correlations between CT texture and staining intensity.Results:SD and MPP quantified from medium to coarse texture on contrast-enhanced CT images showed significant associations with the average intensity of tumor staining with pimonidazole (for SD: filter value, 2.5; slope = 0.003; P = .0003). UPP (medium to coarse texture) on unenhanced CT images showed a significant inverse association with tumor Glut-1 expression (filter value, 2.5; slope = -115.13; P = .0008). MPP quantified from medium to coarse texture on both unenhanced and contrast-enhanced CT images showed significant inverse associations with tumor CD34 expression (unenhanced CT: filter value, 1.8; slope = -0.0008; P = .003; contrast-enhanced CT: filter value, 1.8; slope = -0.0006; P = .004).Conclusion:Texture parameters derived from CT images of NSCLC have the potential to act as imaging correlates for tumor hypoxia and angiogenesis.© RSNA, 2012Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112428/-/DC1.
    Radiology 11/2012; · 6.34 Impact Factor
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    ABSTRACT: Purpose:To determine if computed tomographic (CT) texture features of primary colorectal cancer are related to 5-year overall survival rate.Materials and Methods:Institutional review board waiver was obtained for this retrospective analysis. Texture features of the entire primary tumor were assessed with contrast material-enhanced staging CT studies obtained in 57 patients as part of an ethically approved study and by using proprietary software. Entropy, uniformity, kurtosis, skewness, and standard deviation of the pixel distribution histogram were derived from CT images without filtration and with filter values corresponding to fine (1.0), medium (1.5, 2.0), and coarse (2.5) textures. Patients were followed up until death and were censored at 5 years if they were still alive. Kaplan-Meier analysis was performed to determine the relationship, if any, between CT texture and 5-year overall survival rate. The Cox proportional hazards model was used to assess independence of texture parameters from stage.Results:Follow-up data were available for 55 of 57 patients. There were eight stage I, 19 stage II, 17 stage III, and 11 stage IV cancers. Fine-texture feature Kaplan-Meier survival plots for entropy, uniformity, kurtosis, skewness, and standard deviation of the pixel distribution histogram were significantly different for tumors above and below each respective threshold receiver operating characteristic (ROC) curve optimal cutoff value (P = .001, P = .018, P = .032, P = .008, and P = .001, respectively), with poorer prognosis for ROC optimal values (a) less than 7.89 for entropy, (b) at least 0.01 for uniformity, (c) less than 2.48 for kurtosis, (d) at least -0.38 for skewness, and (e) less than 61.83 for standard deviation. Multivariate Cox proportional hazards regression analysis showed that each parameter was independent from the stage predictor of overall survival rate (P = .001, P = .009, P = .006, P = .02, and P = .001, respectively).Conclusion:Fine-texture features are associated with poorer 5-year overall survival rate in patients with primary colorectal cancer.© RSNA, 2012Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120254/-/DC1.
    Radiology 11/2012; · 6.34 Impact Factor
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    ABSTRACT: BACKGROUND: Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical images METHODS: Image texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods. RESULTS: Early evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice. CONCLUSION: This review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging. TEACHING POINTS : • Tumor spatial heterogeneity is an important prognostic factor. • Image texture analysis is an approach of quantifying heterogeneity. • Different methods can be applied, including statistical-, model-, and transform-based methods. • Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment.
    Insights into imaging. 10/2012;
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    ABSTRACT: Dynamic contrast-enhanced computed tomography (DCE-CT) assesses the vascular support of tumours through analysis of temporal changes in attenuation in blood vessels and tissues during a rapid series of images acquired with intravenous administration of iodinated contrast material. Commercial software for DCE-CT analysis allows pixel-by-pixel calculation of a range of validated physiological parameters and depiction as parametric maps. Clinical studies support the use of DCE-CT parameters as surrogates for physiological and molecular processes underlying tumour angiogenesis. DCE-CT has been used to provide biomarkers of drug action in early phase trials for the treatment of a range of cancers. DCE-CT can be appended to current imaging assessments of tumour response with the benefits of wide availability and low cost. This paper sets out guidelines for the use of DCE-CT in assessing tumour vascular support that were developed using a Delphi process. Recommendations encompass CT system requirements and quality assurance, radiation dosimetry, patient preparation, administration of contrast material, CT acquisition parameters, terminology and units, data processing and reporting. DCE-CT has reached technical maturity for use in therapeutic trials in oncology. The development of these consensus guidelines may promote broader application of DCE-CT for the evaluation of tumour vascularity. Key Points • DCE-CT can robustly assess tumour vascular support • DCE-CT has reached technical maturity for use in therapeutic trials in oncology • This paper presents consensus guidelines for using DCE-CT in assessing tumour vascularity.
    European Radiology 02/2012; 22(7):1430-41. · 4.34 Impact Factor
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    Kenneth Miles
    Cancer Imaging 01/2012; 12:185-6. · 1.59 Impact Factor
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    ABSTRACT: We applied modern molecular and functional imaging to the pretreatment assessment of lung cancer using combined dynamic contrast-enhanced computed tomography (DCE-CT) and (18)F-fluorodeoxyglucose-positron emission tomography ((18)F-FDG-PET) to phenotype tumors. Seventy-four lung cancer patients were prospectively recruited for (18)F-FDG-PET/DCE-CT using PET/64-detector CT. After technical failures, there were 64 patients (35 males, 29 females; mean age [± SD] 67.5 ± 7.9 years). DCE-CT yielded tumor peak enhancement (PE) and standardized perfusion value (SPV). The uptake of (18)F-FDG quantified on PET as the standardized uptake value (SUV(max)) assessed tumor metabolism. The median values for SUV(max) and SPV were used to define four vascular-metabolic phenotypes. There were associations (Spearman rank correlation [rs]) between tumor size and vascular-metabolic parameters: SUV(max) versus size (rs  =  .40, p  =  .001) and SUV/PE versus size (r  =  .43, p < .001). Patients with earlier-stage (I-IIA, n  =  30) disease had mean (± SD) SUV/PE 0.36 ± 0.28 versus 0.56 ± 0.32 in later-stage (stage IIB-IV, n  =  34) disease (p  =  .007). The low metabolism with high vascularity phenotype was significantly more common among adenocarcinomas (p  =  .018), whereas the high metabolism with high vascularity phenotype was more common among squamous cell carcinomas (p  =  .024). Other non-small cell lung carcinoma tumor types demonstrated a high prevalence of the high metabolism with low vascularity phenotype (p  =  .028). We show that tumor subtypes have different vascular-metabolic associations, which can be helpful clinically in managing lung cancer patients to hone targeted therapy.
    Molecular Imaging 01/2012; 11(5):353-60. · 3.41 Impact Factor

Publication Stats

540 Citations
131.59 Total Impact Points

Institutions

  • 2014
    • Guy's and St Thomas' NHS Foundation Trust
      Londinium, England, United Kingdom
  • 2008–2014
    • University College London
      • • Institute of Nuclear Medicine
      • • Department of Metabolism and Experimental Therapeutics
      Londinium, England, United Kingdom
  • 2013
    • University of Queensland 
      • Department of Medicine
      Brisbane, Queensland, Australia
  • 2012–2013
    • Princess Alexandra Hospital (Queensland Health)
      Brisbane, Queensland, Australia
  • 2007–2012
    • Brighton and Sussex Medical School
      • Clinical Imaging Sciences Centre (CISC)
      Brighton, England, United Kingdom
  • 2004–2012
    • University of Sussex
      • • Clinical Imaging Sciences Centre
      • • Department of Engineering and Design
      Brighton, ENG, United Kingdom
  • 2010–2011
    • Brighton and Sussex University Hospitals NHS Trust
      Brighton, England, United Kingdom
    • The Hillingdon Hospitals NHS Foundation Trust
      अक्सब्रिज, England, United Kingdom