John Dickson

Bio: John Dickson is an academic researcher from University College London. The author has contributed to research in topics: Positron emission tomography & Medicine. The author has an hindex of 33, co-authored 98 publications receiving 5049 citations. Previous affiliations of John Dickson include University of Pretoria & University College London Hospitals NHS Foundation Trust.

Imaging biomarker roadmap for cancer studies.

Abstract: Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.

Functional imaging of neuroendocrine tumors with combined PET/CT using 68Ga-DOTATATE (DOTA-DPhe1,Tyr3-octreotate) and 18F-FDG

Abstract: BACKGROUND. The aim was to assess the relevant distribution of the novel PET tracer 68Ga-DOTATATE in neuroendocrine tumors (NETs) with combined positron emission tomography / computed tomography (PET/CT) and compare its performance with that of 18F-FDG PET/CT. METHODS. The imaging findings with 68Ga-DOTATATE and 18F-FDG on 38 consecutive patients with a diagnosis of primary or recurrent NET were compared and correlated with tumor grade on histology based on ki67 and mitotic index. RESULTS. The sensitivity of 68Ga-DOTATATE PET/CT was 82% (31 of 38) and that of 18F-FDG PET/CT was 66% (25 of 38). The sensitivity of combined 68Ga-DOTATATE and 18F-FDG PET/CT was 92% (35 of 38). There was greater uptake of 68Ga-DOTATATE than 18F-FDG in low-grade NET (median SUV 29 vs 2.9, P < .001). In high-grade NET there was higher uptake of 18F-FDG over 68Ga-DOTATATE (median SUV 11.7 vs 4.4, P = .03). There was a significant correlation with predominant tumor uptake of 68Ga-DOTATATE or 18F-FDG and tumor grade on histology (P < .0001). CONCLUSIONS. 68Ga-DOTATATE PET/CT is a useful novel imaging modality for NETs and is superior to 18F-FDG for imaging well-differentiated NET. Functional imaging with both 68Ga-DOTATATE and 18F-FDG has potential for a more comprehensive tumor assessment in intermediate- and high-grade tumors. Cancer 2008. ©2008 American Cancer Society.

Global patient outcomes after elective surgery: Prospective cohort study in 27 low-, middle- and high-income countries

Abstract: Background As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. Methods We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. Results A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2–7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. Conclusions Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care.

Exenatide and the treatment of patients with Parkinson’s disease

Abstract: Background. There is increasing interest in methods to more rapidly and cost-efficiently investigate drugs that are approved for clinical use in the treatment of another condition. Exenatide is a type 2 diabetes treatment that has been shown to have neuroprotective/neurorestorative properties in preclinical models of neurodegeneration. Methods. As a proof of concept, using a single-blind trial design, we evaluated the progress of 45 patients with moderate Parkinson’s disease (PD), randomly assigned to receive subcutaneous exenatide injection for 12 months or to act as controls. Their PD was compared after overnight withdrawal of conventional PD medication using blinded video assessment of the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), together with several nonmotor tests, at baseline, 6 months, and 12 months and after a further 2-month washout period (14 months). Results. Exenatide was well tolerated, although weight loss was common and l-dopa dose failures occurred in a single patient. Single-blinded rating of the exenatide group suggested clinically relevant improvements in PD across motor and cognitive measures compared with the control group. Exenatide-treated patients had a mean improvement at 12 months on the MDS-UPDRS of 2.7 points, compared with mean decline of 2.2 points in control patients (P = 0.037). Conclusion. These results demonstrate a potential cost-efficient approach through which preliminary clinical data of possible biological effects are obtainable, prior to undertaking the major investment required for double-blind trials of a potential disease-modifying drug in PD. Trial registration. Clinicaltrials.gov NCT01174810. Funding. Cure Parkinson’s Trust.

Artificial intelligence in radiology

Abstract: Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Abstract: Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue.

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Abstract: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.