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Jeffrey L. Evelhoch

Bio: Jeffrey L. Evelhoch is an academic researcher from Merck & Co.. The author has contributed to research in topics: Magnetic resonance imaging & In vivo. The author has an hindex of 37, co-authored 99 publications receiving 8802 citations. Previous affiliations of Jeffrey L. Evelhoch include United States Military Academy & Lincoln's Inn.


Papers
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Journal ArticleDOI
TL;DR: A standard set of quantity names and symbols related to the estimation of kinetic parameters from dynamic contrast‐enhanced T1‐weighted magnetic resonance imaging data, using diffusable agents such as gadopentetate dimeglumine (Gd‐DTPA), are described.
Abstract: We describe a standard set of quantity names and symbols related to the estimation of kinetic parameters from dynamic contrast-enhanced T(1)-weighted magnetic resonance imaging data, using diffusable agents such as gadopentetate dimeglumine (Gd-DTPA). These include a) the volume transfer constant K(trans) (min(-1)); b) the volume of extravascular extracellular space (EES) per unit volume of tissue v(e) (0 < v(e) < 1); and c) the flux rate constant between EES and plasma k(ep) (min(-1)). The rate constant is the ratio of the transfer constant to the EES (k(ep) = K(trans)/v(e)). Under flow-limited conditions K(trans) equals the blood plasma flow per unit volume of tissue; under permeability-limited conditions K(trans) equals the permeability surface area product per unit volume of tissue. We relate these quantities to previously published work from our groups; our future publications will refer to these standardized terms, and we propose that these be adopted as international standards.

3,078 citations

Journal ArticleDOI
TL;DR: Experts assembled to review, debate and summarize the challenges of IB validation and qualification produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical validation, biological/clinical validation and assessment of cost-effectiveness.
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.

758 citations

Journal ArticleDOI
TL;DR: The outcome of a workshop that considered the methodology and design of magnetic resonance studies is reported, recommending how this new tool might best be used.
Abstract: Vascular and angiogenic processes provide an important target for novel cancer therapeutics. Dynamic contrast-enhanced magnetic resonance imaging is being used increasingly to noninvasively monitor the action of these therapeutics in early-stage clinical trials. This publication reports the outcome of a workshop that considered the methodology and design of magnetic resonance studies, recommending how this new tool might best be used.

513 citations

Journal ArticleDOI
TL;DR: Several aspects of data acquisition should be taken into account when developing protocols for DCE‐MRI regardless of how the data are analyzed, including the relationship between signal enhancement and contrastAgent concentration, intra‐ or inter‐patient variation in the blood contrast agent concentration as a function of time.
Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has recently emerged as a promising method for both diagnosis and prognosis of cancer despite considerable variation in both the methods of data acquisition and analysis. Both to facilitate integration of results from multiple institutions and to ensure that the data reflect the underlying physiology as accurately as possible, several aspects of data acquisition should be taken into account when developing protocols for DCE-MRI regardless of how the data are analyzed. Among the relevant issues are the relationship between signal enhancement and contrast agent concentration, intra- or inter-patient variation in the blood contrast agent concentration as a function of time, requirements for spatial and temporal resolution, the impact of tumor heterogeneity, and the impact of patient motion during the study. This review considers these factors and, when possible, makes specific recommendations for addressing them experimentally.

391 citations

Journal ArticleDOI
TL;DR: Each type and grade of tumor is a metabolically hetero-geneous group and the hypothesis that mobile lipids observed in vivo in 1H-MR spectroscopy may correlate independently with prognosis of individual patients is hypotheses.
Abstract: The authors represent a cooperative group of 15 institutions that examined the feasibility of using metabolic features observed in vivo with 1H-magnetic resonance (MR) spectroscopy to characterize brain tumors of the glial type. The institutions provided blinded, centralized MR spectroscopy data processing long with independent central review of MR spectroscopy voxel placement, composition and contamination by brain, histopathological typing using current World Health Organization criteria, and clinical data. Proton 1H-MR spectroscopy was performed using a spin-echo technique to obtain spectra from 8-cc voxels in the tumor and when feasible in the contralateral brain. Eighty-six cases were assessable, 41 of which had contralateral brain spectra. Glial tumors had significantly elevated intensities of choline signals, decreased intensities of creatine signals, and decreased intensities of N-acetylaspartate compared to brain. Choline signal intensities were highest in astrocytomas and anaplastic astrocytomas, and creatine signal intensities were lowest in glioblastomas. However, whether expressed relative to brain or as intratumoral ratios, these metabolic characteristics exhibited large variations within each subtype of glial tumor. The resulting overlaps precluded diagnostic accuracy in the distinction of low-and high-grade tumors. Although the extent of contamination of the 1H-MR spectroscopy voxel by brain had a marked effect on metabolite concentrations and ratios, selection of cases with minimal contamination did not reduce these overlaps. Thus, each type and grade of tumor is a metabolically hetero-geneous group. Lactate occurred infrequently and in all grades. Mobile lipids, on the other hand, occurred in 41% of high-grade tumors with higher mean amounts found in glioblastomas. This result, coupled with the recent demonstration that intratumoral mobile lipids correlate with microscopic tumor cell necrosis, leads to the hypothesis that mobile lipids observed in vivo in 1H-MR spectroscopy may correlate independently with prognosis of individual patients.

360 citations


Cited by
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TL;DR: This research framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms and envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD.
Abstract: In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a "research framework" because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

5,126 citations

Journal Article
TL;DR: Current knowledge of blood flow and perfusion-related parameters, which usually go hand in hand and in turn define the cellular metabolic microenvironment of human malignancies, are summarized for predicting the acute and/or long-term response of tumors to therapy.
Abstract: The objective of this review article is to summarize current knowledge of blood flow and perfusion-related parameters, which usually go hand in hand and in turn define the cellular metabolic microenvironment of human malignancies. A compilation of available data from the literature on blood flow, oxygen and nutrient supply, and tissue oxygen and pH distribution in human tumors is presented. Whenever possible, data obtained for human tumors are compared with the respective parameters in normal tissues, isotransplanted or spontaneous rodent tumors, and xenografted human tumors. Although data on human tumors in situ are scarce and there may be significant errors associated with the techniques used for measurements, experimental evidence is provided for the existence of a compromised and anisotropic blood supply to many tumors. As a result, O2-depleted areas develop in human malignancies which coincide with nutrient and energy deprivation and with a hostile metabolic microenvironment (e.g., existence of severe tissue acidosis). Significant variations in these relevant parameters must be expected between different locations within the same tumor, at the same location at different times, and between individual tumors of the same grading and staging. Furthermore, this synopsis will attempt to identify relevant pathophysiological parameters and other related areas future research of which might be most beneficial for designing individually tailored treatment protocols with the goal of predicting the acute and/or long-term response of tumors to therapy.

3,379 citations

Journal ArticleDOI
TL;DR: A standard set of quantity names and symbols related to the estimation of kinetic parameters from dynamic contrast‐enhanced T1‐weighted magnetic resonance imaging data, using diffusable agents such as gadopentetate dimeglumine (Gd‐DTPA), are described.
Abstract: We describe a standard set of quantity names and symbols related to the estimation of kinetic parameters from dynamic contrast-enhanced T(1)-weighted magnetic resonance imaging data, using diffusable agents such as gadopentetate dimeglumine (Gd-DTPA). These include a) the volume transfer constant K(trans) (min(-1)); b) the volume of extravascular extracellular space (EES) per unit volume of tissue v(e) (0 < v(e) < 1); and c) the flux rate constant between EES and plasma k(ep) (min(-1)). The rate constant is the ratio of the transfer constant to the EES (k(ep) = K(trans)/v(e)). Under flow-limited conditions K(trans) equals the blood plasma flow per unit volume of tissue; under permeability-limited conditions K(trans) equals the permeability surface area product per unit volume of tissue. We relate these quantities to previously published work from our groups; our future publications will refer to these standardized terms, and we propose that these be adopted as international standards.

3,078 citations