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The aim was to evaluate volume, diffusion, and perfusion metrics for better presurgical differentiation between high-grade gliomas (HGG), low-grade gliomas (LGG), and metastases (MET). For this retrospective study, 43 patients with histologically verified intracranial HGG (n = 18), LGG (n = 10), and MET (n = 15) were chosen. Preoperative magnetic resonance data included pre- and post-gadolinium contrast-enhanced T1-weighted fluid-attenuated inversion recover, cerebral blood flow (CBF), cerebral blood volume (CBV), fractional anisotropy, and apparent diffusion coefficient maps used for quantification of magnetic resonance biometrics by manual delineation of regions of interest. A binary logistic regression model was applied for multiparametric analysis and receiver operating characteristic (ROC) analysis. Statistically significant differences were found for normalized-ADC-tumor (nADC-T), normalized-CBF-tumor (nCBF-T), normalized-CBV-tumor (nCBV-T), and normalized-CBF-edema (nCBF-E) between LGG and HGG, and when these metrics were combined, HGG could be distinguished from LGG with a sensitivity and specificity of 100%. The only metric to distinguish HGG from MET was the normalized-ADC-E with a sensitivity of 68.8% and a specificity of 80%. LGG can be distinguished from MET by combining edema volume (Vol-E), Vol-E/tumor volume (Vol-T), nADC-T, nCBF-T, nCBV-T, and nADC-E with a sensitivity of 93.3% and a specificity of 100%. The present study confirms the usability of a multibiometric approach including volume, perfusion, and diffusion metrics in differentially diagnosing brain tumors in preoperative patients and adds to the growing body of evidence in the clinical field in need of validation and standardization.

Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for [Formula: see text] in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.

OBJECTIVES/SPECIFIC AIMS: The study aims to understand if pro inflammatory epicardial white adipose phenotype is positively associated with coronary atherosclerosis, while the brown adipose phenotype is negatively associated. Primary outcome is association between epicardial fat fraction and coronary atherosclerosis and cardiac function. Secondary outcome is transcriptomic and lipidomic profiling between epicardial, extra pericardial, and subcutaneous depots and how these profiles correlate with fat fraction. METHODS/STUDY POPULATION: Recruited patients undergoing open-heart surgery provided informed consent at their second visit and underwent laboratory testing and imaging (cardiac magnetic resonance including water-fat imaging and coronary calcium computed tomography) prior to their surgery. Cardiac function such as cardiac chamber volume, mass, function, and strain, and depo-specific fat fraction were calculated from cardiac MR and Agatston calcium score and epicardial adipose volume from CT images. At the time of surgery, a tissue specimens from the epicardial, extrapericardial, and subcutaneous depots were obtained for transcriptomic and lipidomic analysis. Linear and logistic regression analyses adjusted for other variables were performed to evaluate significance level between variables. RESULTS/ANTICIPATED RESULTS: 37 subjects were enrolled in the study, 13 (35%) of which were women. Cardiac function and fat fraction was quantified in all patients, whereas tissue analyses were performed in 22 patients. Epicardial and extrapericardial fat fraction were independently associated with coronary atherosclerosis (p-value 0.01 and 0.04 respectively) Only epicardial fat fraction was negatively associated with global circumferential shortening of the left ventricle (0.03), while neither the extrapericardial fat fraction nor epicardial adipose volume were not (p =0.33 and 0.97 respectively) All three adipose depots have unique gene signatures with differentially expressed genes and pathways. RNA sequencing of epicardial, extrapericardial, and subcutaneous depots demonstrated tight clustering of epicardial and subcutaneous signatures based on PCA analysis (Figure 2). 19 lipid classes and 59 lipids showed differential expression between at least 2 of the fat depots (Figure 3). Hierarchal clustering of the lipids showed that epicardial and extrapericardial depots were more closely related than subcutaneous adipose. Plasmenyl-phosphatidylcholines, with an ether-linked fatty acid at the sn-1 position of the lipid, were higher in subcutaneous fat while most other lipids were higher in epicardial fat per tissue weight, such as ceramides (p=0.002). DISCUSSION/SIGNIFICANCE OF IMPACT: Epicardial, extrapericardial, and subcutaneous adipose depots express different lipidome and transcriptome signatures and different pathways. GSEA analysis demonstrated enrichment of genes related to antigen presentation and B cell immunity in epicardial compared to subcutaneous adipose tissue. Epicardial fat fraction is associated with coronary atherosclerosis and decreased left ventricular global circumferential shortening as an early predictor of decreased left ventricular stroke volume. Epicardial fat fraction is also associated with cermides which may play role in the development of coronary atherosclerosis and decreased cardiac function.

Technologic advances enable performance of diffusion-weighted imaging (DWI) at ultrahigh b-values, where standard monoexponential model analysis may not apply. Rather, non-Gaussian water diffusion properties emerge, which in cellular tissues are, in part, influenced by the intracellular environment that is not well evaluated by conventional DWI. The novel technique, diffusion kurtosis imaging (DKI), enables characterization of non-Gaussian water diffusion behavior. More advanced mathematical curve fitting of the signal intensity decay curve using the DKI model provides an additional parameter Kapp that presumably reflects heterogeneity and irregularity of cellular microstructure, as well as the amount of interfaces within cellular tissues. Although largely applied for neural applications over the past decade, a small number of studies have recently explored DKI outside the brain. The most investigated organ is the prostate, with preliminary studies suggesting improved tumor detection and grading using DKI. Although still largely in the research phase, DKI is being explored in wider clinical settings. When assessing extracranial applications of DKI, careful attention to details with which body radiologists may currently be unfamiliar is important to ensure reliable results. Accordingly, a robust understanding of DKI is necessary for radiologists to better understand the meaning of DKI-derived metrics in the context of different tumors and how these metrics vary between tumor types and in response to treatment. In this review, we outline DKI principles, propose biostructural basis for observations, provide a comparison with standard monoexponential fitting and the apparent diffusion coefficient, report on extracranial clinical investigations to date, and recommend technical considerations for implementation in body imaging.

Purpose: To evaluate between-site agreement of apparent diffusion coefficient (ADC) measurements in preclinical magnetic resonance imaging (MRI) systems. Materials and Methods: A miniaturized thermally stable ice-water phantom was devised. ADC (mean and interquartile range) was measured over several days, on 4.7T, 7T, and 9.4T Bruker, Agilent, and Magnex small-animal MRI systems using a common protocol across seven sites. Day-to-day repeatability was expressed as percent variation of mean ADC between acquisitions. Cross-site reproducibility was expressed as 1.96 x standard deviation of percent deviation of ADC values. Results: ADC measurements were equivalent across all seven sites with a cross-site ADC reproducibility of 6.3%. Mean day-to-day repeatability of ADC measurements was 2.3%, and no site was identified as presenting different measurements than others (analysis of variance [ANOVA] P = 0.02, post-hoc test n.s.). Between-slice ADC variability was negligible and similar between sites (P = 0.15). Mean within-region-of-interest ADC variability was 5.5%, with one site presenting a significantly greater variation than the others (P = 0.0013). Conclusion: Absolute ADC values in preclinical studies are comparable between sites and equipment, provided standardized protocols are employed.

Purpose To evaluate a gradient nonlinearity correction (GNC) program for quantitative apparent diffusion coefficient (ADC) measurements on phantom and human subject diffusion-weighted (DW) magnetic resonance imaging (MRI) scans in a multicenter breast cancer treatment response study Materials and Methods A GNC program using fifth-order spherical harmonics for gradient modeling was applied retrospectively to qualification phantom and human subject scans. Ice-water phantoms of known diffusion coefficient were scanned at five different study centers with different scanners and receiver coils. Human in vivo data consisted of baseline and early-treatment exams on 54 patients from four sites. ADC maps were generated with and without GNC. Regions of interest were defined to quantify absolute errors and changes with GNC over breast imaging positions. Results Phantom ADC errors varied with region of interest (ROI) position and scanner configuration; the mean error by configuration ranged from 1.4% to 19.9%. GNC significantly reduced the overall mean error for all sites from 9.9% to 0.6% (P = 0.016). Spatial dependence of GNC was highest in the right-left (RL) and anterior-posterior (AP) directions. Human subject mean tumor ADC was reduced 0.2 to 12% by GNC at different sites. By regression, every 1-cm change in tumor ROI position between baseline and follow-up visits resulted in an estimated change of 2.4% in the ADC early-treatment response measurement. Conclusion GNC is effective for removing large, system-dependent errors in quantitative breast DWI. GNC may be important in ensuring reproducibility in multicenter studies and in reducing errors in longitudinal treatment response measures arising from spatial variations in tumor position between visits. J. Magn. Reson. Imaging 2015;42:908–919.

Intrathoracic fat volume, more specifically, epicardial fat volume, is an emerging imaging biomarker of adverse cardiovascular events. The purpose of this work is to show the feasibility and reproducibility of intrathoracic fat volume measurement applied to contrast-enhanced multidetector computed tomography images. A retrospective cohort study of 62 subjects free of cardiovascular disease (55% females, age = 49 ± 11 years) conducted from 2008 to 2011 formed the study group. Intrathoracic fat volume was defined as all fat voxels measuring −50 to −250 Hounsfield Unit within the intrathoracic cavity from the level of the pulmonary artery bifurcation to the heart apex. The intrathoracic fat was separated into epicardial and extrapericardial fat by tracing the pericardium. The measurements were obtained by 2 readers and compared for interrater reproducibility. The fat volume measurements for the study group were 141 ± 72 cm3 for intrathoracic fat, 58 ± 27 cm3 for epicardial fat, and 84 ± 50 cm3 for extrapericardial fat. There was no statistically significant difference in intrathoracic fat volume measurements between the 2 readers, with correlation coefficients of 0.88 (P = .55) for intrathoracic fat volume and −0.12 (P = .33) for epicardial fat volume. Voxel-based measurement of intrathoracic fat, including the separation into epicardial and extrapericardial fat, is feasible and highly reproducible from multidetector computed tomography scans.

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi-institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application-specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48-61, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

PURPOSE: To determine the in-vitro accuracy, test-retest repeatability and interplatform reproducibility of T(1) quantification protocols used for DCE-MRI at 1.5T and 3.0T. METHODS: A T(1) phantom with 14 samples was imaged at 8 centers with a common inversion recovery spin echo (IR-SE) protocol and a variable flip angle (VFA) protocol using 7 flip angles (FA), as well as site-specific protocols [VFA with different FA, variable TR (VTR), proton density (PD) and Look-Locker IR]. Factors influencing accuracy (deviation from reference NMR T(1) measurements) and repeatability were assessed using general linear mixed models. Interplatform reproducibility was assessed using coefficients of variation (CV). RESULTS: For the common IR-SE protocol, accuracy (median error across platforms=1.4%–5.5%) was influenced predominantly by T(1) sample (P

PURPOSE: In the current study we examined the ability of diffusion MRI (dMRI) to predict pathologic response in pancreatic cancer patients receiving neoadjuvant chemoradiation. METHODS: We performed a prospective pilot study of dMRI in patients with resectable pancreatic cancer. Patients underwent dMRI prior to neoadjuvant chemoradiation. Surgical specimens were graded according to the percent tumor cell destruction. Apparent diffusion coefficient (ADC) maps were used to generate whole-tumor derived ADC histogram distributions and mean ADC values. The primary objective of the study was to correlate ADC parameters with pathologic and CT response. RESULTS: Ten of the 12 patients enrolled on the study completed chemoradiation and had surgery. Three were found to be unresectable at the time of surgery and no specimen was obtained. Out of the 7 patients who underwent pancreaticoduodenectomy, 3 had a grade III histopathologic response (> 90% tumor cell destruction), 2 had a grade IIB response (51% to 90% tumor cell destruction), 1 had a grade IIA response (11% to 50% tumor cell destruction), and 1 had a grade I response (> 90% viable tumor). Median survival for patients with a grade III response, grade I-II response, and unresectable disease were 25.6, 18.7, and 6.1 months, respectively. There was a significant correlation between pre-treatment mean tumor ADC values and the amount of tumor cell destruction after chemoradiation with a Pearson correlation coefficient of 0.94 (P = .001). Mean pre-treatment ADC was 161 × 10− 5 mm2/s (n = 3) in responding patients (> 90% tumor cell destruction) compared to 125 × 10− 5 mm2/s (n = 4) in non-responding patients (> 10% viable tumor). CT imaging showed no significant change in tumor size in responders or non-responders. CONCLUSIONS: dMRI may be useful to predict response to chemoradiation in pancreatic cancer. In our study, tumors with a low ADC mean value at baseline responded poorly to standard chemoradiation and would be candidates for intensified therapy.

In this article, we review the clinical applications of diffusion magnetic resonance imaging (MRI) in the radiotherapy treatment of several key clinical sites, including those of the central nervous system, the head and neck, the prostate, and the cervix. Diffusion-weighted MRI (DWI) is an imaging technique that is rapidly gaining widespread acceptance owing to its ease and wide availability. DWI measures the mobility of water within tissue at the cellular level without the need of any exogenous contrast agent. For radiotherapy treatment planning, DWI improves upon conventional imaging techniques, by better characterization of tumor tissue properties required for tumor grading, diagnosis, and target volume delineation. Because DWI is also a sensitive marker for alterations in tumor cellularity, it has potential clinical applications in the early assessment of treatment response following radiation therapy.

Pharmacokinetic analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) time-course data allows estimation of quantitative parameters such as K (trans) (rate constant for plasma/interstitium contrast agent transfer), v e (extravascular extracellular volume fraction), and v p (plasma volume fraction). A plethora of factors in DCE-MRI data acquisition and analysis can affect accuracy and precision of these parameters and, consequently, the utility of quantitative DCE-MRI for assessing therapy response. In this multicenter data analysis challenge, DCE-MRI data acquired at one center from 10 patients with breast cancer before and after the first cycle of neoadjuvant chemotherapy were shared and processed with 12 software tools based on the Tofts model (TM), extended TM, and Shutter-Speed model. Inputs of tumor region of interest definition, pre-contrast T1, and arterial input function were controlled to focus on the variations in parameter value and response prediction capability caused by differences in models and associated algorithms. Considerable parameter variations were observed with the within-subject coefficient of variation (wCV) values for K (trans) and v p being as high as 0.59 and 0.82, respectively. Parameter agreement improved when only algorithms based on the same model were compared, e.g., the K (trans) intraclass correlation coefficient increased to as high as 0.84. Agreement in parameter percentage change was much better than that in absolute parameter value, e.g., the pairwise concordance correlation coefficient improved from 0.047 (for K (trans)) to 0.92 (for K (trans) percentage change) in comparing two TM algorithms. Nearly all algorithms provided good to excellent (univariate logistic regression c-statistic value ranging from 0.8 to 1.0) early prediction of therapy response using the metrics of mean tumor K (trans) and k ep (=K (trans)/v e, intravasation rate constant) after the first therapy cycle and the corresponding percentage changes. The results suggest that the interalgorithm parameter variations are largely systematic, which are not likely to significantly affect the utility of DCE-MRI for assessment of therapy response.

Purpose To describe an efficient procedure to empirically characterize gradient nonlinearity and correct for the corresponding apparent diffusion coefficient (ADC) bias on a clinical magnetic resonance imaging (MRI) scanner. Materials and Methods Spatial nonlinearity scalars for individual gradient coils along superior and right directions were estimated via diffusion measurements of an isotropic ice-water phantom. Digital nonlinearity model from an independent scanner, described in the literature, was rescaled by system-specific scalars to approximate 3D bias correction maps. Correction efficacy was assessed by comparison to unbiased ADC values measured at isocenter. Results Empirically estimated nonlinearity scalars were confirmed by geometric distortion measurements of a regular grid phantom. The applied nonlinearity correction for arbitrarily oriented diffusion gradients reduced ADC bias from ∼20% down to ∼2% at clinically relevant offsets both for isotropic and anisotropic media. Identical performance was achieved using either corrected diffusion-weighted imaging (DWI) intensities or corrected b-values for each direction in brain and ice-water. Direction-average trace image correction was adequate only for isotropic medium. Conclusion Empiric scalar adjustment of an independent gradient nonlinearity model adequately described DWI bias for a clinical scanner. Observed efficiency of implemented ADC bias correction quantitatively agreed with previous theoretical predictions and numerical simulations. The described procedure provides an independent benchmark for nonlinearity bias correction of clinical MRI scanners. J. Magn. Reson. Imaging 2014;40:1487–1495. © 2013 Wiley Periodicals, Inc.

Rationale and Objectives: To investigate for differences in metabolic concentrations and ratios between patients with systemic lupus erythematosus (SLE) without (group SLE) and those with neurological symptoms (group NPSLE) compared to a healthy control (group HC) in three normal-appearing brain regions: the frontal white matter, right insula (RI), and occipital gray matter and whether changes in any of the metabolites or metabolic ratios are correlated to disease activity and other clinical parameters. Materials and Methods: Twenty patients with SLE (18 women and 2 men, age range 23.4-64.6 years, mean age 43.9 years), 23 NPSLE patients (23 women, age range 23.7-69.8 years, mean age 42.4 years), and 21 HC (19 women and 2 men, age range 21.0-65.7 years, mean age 43.4 years) were included. All subjects had conventional brain magnetic resonance imaging and H-1 single-voxel spectroscopy, clinical assessment, and laboratory testing. Results: NPSLE patients had significantly reduced N-acetylaspartate (NAA)/creatine compared to HC (P = .02) and SLE patients (P = .01) in the RI. Lower glutamine/creatine levels were also detected in RI in both patient groups and in frontal white matter in NPSLE patients compared to HC (P = .01, P = .02). NAA/Cr ratio in the RI was significantly negatively correlated with the Systemic Lupus Erythematosus Disease Activity Index (r = -0.41; P = .008), and patients with active SLE symptoms also had a trend toward lower NAA/creatine ratios (1.02 vs 1.12; P = .07). Conclusions: The present data support previous findings of abnormal metabolic changes in normal-appearing regions in the brain of both SLE and NPSLE patients and raise the possibility that especially NAA, glutamine, and glutamate may be additional biomarkers for cerebral disease activity in SLE patients as these early metabolic changes occur in the brain of SLE patients before neurologic and imaging manifestations become apparent. (Less)

RATIONALE: Treatment of glioblastoma (GBM) remains challenging due in part to its histologic intratumoral heterogeneity that contributes to its overall poor treatment response. Our goal was to evaluate a voxel-based biomarker, the functional diffusion map (fDM), as an imaging biomarker to detect heterogeneity of tumor response in a radiation dose escalation protocol using a genetically engineered murine GBM model. EXPERIMENTAL DESIGN: Twenty-four genetically engineered murine GBM models [Ink4a-Arf-/-/Ptenloxp/loxp/Ntv-a RCAS/PDGF(+)/Cre(+)] were randomized in four treatment groups (n = 6 per group) consisting of daily doses of 0, 1, 2, and 4 Gy delivered for 5 days. Contrast-enhanced T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scans were acquired for tumor delineation and quantification of apparent diffusion coefficient (ADC) maps, respectively. MRI experiments were performed daily for a week and every 2 days thereafter. For each animal, the area under the curve (AUC) of the percentage change of the ADC (AUCADC) and that of the increase in fDM values (AUCfDM+) were determined within the first 5 days following therapy initiation. RESULTS: Animal survival increased with increasing radiation dose. Treatment induced a dose-dependent increase in tumor ADC values. The strongest correlation between survival and ADC measurements was observed using the AUCfDM+ metric (R2 = 0.88). CONCLUSION: This study showed that the efficacy of a voxel-based imaging biomarker (fDM) was able to detect spatially varying changes in tumors, which were determined to be a more sensitive predictor of overall response versus whole-volume tumor measurements (AUCADC). Finally, fDM provided for visualization of treatment-associated spatial heterogeneity within the tumor.

Purpose Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10–20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Magn Reson Med 71:1312–1323, 2014. © 2013 Wiley Periodicals, Inc.

PURPOSE: The inherent treatment resistance of glioblastoma (GBM) can involve multiple mechanisms including checkpoint kinase (Chk1/2)-mediated increased DNA repair capability, which can attenuate the effects of genotoxic chemotherapies and radiation. The goal of this study was to evaluate diffusion-weighted magnetic resonance imaging (DW-MRI) as a biomarker for Chk1/2 inhibitors in combination with radiation for enhancement of treatment efficacy in GBM. EXPERIMENTAL DESIGN: We evaluated a specific small molecule inhibitor of Chk1/2, AZD7762, in combination with radiation using in vitro human cell lines and in vivo using a genetically engineered GBM mouse model. DW-MRI and T1-contrast MRI were used to follow treatment effects on intracranial tumor cellularity and growth rates, respectively. RESULTS: AZD7762 inhibited clonal proliferation in a panel of GBM cell lines and increased radiosensitivity in p53-mutated GBM cell lines to a greater extent compared to p53 wild-type cells. In vivo efficacy of AZD7762 demonstrated a dose-dependent inhibitory effect on GBM tumor growth rate and a reduction in tumor cellularity based on DW-MRI scans along with enhancement of radiation efficacy. CONCLUSION: DW-MRI was found to be a useful imaging biomarker for the detection of radiosensitization through inhibition of checkpoint kinases. Chk1/2 inhibition resulted in antiproliferative activity, prevention of DNA damage-induced repair, and radiosensitization in preclinical GBM tumor models, both in vitro and in vivo. The effects were found to be maximal in p53-mutated GBM cells. These results provide the rationale for integration of DW-MRI in clinical translation of Chk1/2 inhibition with radiation for the treatment of GBM.

Intravenous gadoxetate disodium can result in acute transient dyspnea that can have a deleterious effect on arterial phase MR image quality and occurs significantly more often than with intravenous gadobenate dimeglumine.

SummaryContext Partial lipodystrophy (PL) is associated with metabolic co-morbidities but may go undiagnosed as the disease spectrum is not fully described. Objective The objective of the study was to define disease spectrum in PL using genetic, clinical (historical, morphometric) and laboratory characteristics. Design Cross-sectional evaluation. Participants Twenty-three patients (22 with familial, one acquired, 78·3% female, aged 12–64 years) with PL and non-alcoholic fatty liver disease (NAFLD). Measurements Genetic, clinical and laboratory characteristics, body composition indices, liver fat content by magnetic resonance imaging (MRI), histopathological and immunofluorescence examinations of liver biopsies. Results Seven patients displayed heterozygous pathogenic variants in LMNA. Two related patients had a heterozygous, likely pathogenic novel variant of POLD1 (NM002691·3: c.3199 G>A; p.E1067K). Most patients had high ratios (>1·5) of percentage fat trunk to percentage fat legs (FMR) when compared to reference normals. Liver fat quantified using MR Dixon method was high (11·3 ± 6·3%) and correlated positively with haemoglobin A1c and triglycerides while leg fat by dual-energy X-ray absorptiometry (DEXA) correlated negatively with triglycerides. In addition to known metabolic comorbidities; chronic pain (78·3%), hypertension (56·5%) and mood disorders (52·2%) were highly prevalent. Mean NAFLD Activity Score (NAS) was 5 ± 1 and 78·3% had fibrosis. LMNA-immunofluorescence staining from select patients (including one with the novel POLD1 variant) showed a high degree of nuclear atypia and disorganization. Conclusions Partial lipodystrophy is a complex multi-system disorder. Metabolic parameters correlate negatively with extremity fat and positively with liver fat. DEXA-based FMR may prove useful as a diagnostic tool. Nuclear disorganization and atypia may be a common biomarker even in the absence of pathogenic variants in LMNA.

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.

The objective of this study was to assess the uncertainty in T1 measurement, by estimating the repeatability coefficient (RC) from two repeated scans, in normal appearing brain tissues employing two different T1 mapping methods. All brain MRI scans were performed on a 3 T MR scanner in 10 patients who had low grade/benign tumors and partial brain radiation therapy (RT) without chemotherapy, at pre-RT, 3 weeks into RT, end RT (6 weeks) and 11, 33, and 85 weeks after RT. T1-weighted images were acquired using (1) a spoiled gradient echo sequence with two flip angles (2FA: 5° and 15°) and (2) a progressive saturation recovery sequence (pSR) with five different TR values (100–2000 ms). Manually drawn volumes of interest (VOIs) included left and right normal putamen and thalamus in gray matter, and frontal and parietal white matter, which were distant from tumors and received a total of accumulated radiation doses less than 5 Gy at 3 weeks. No significant changes or even trends in mean T1 from pre-RT to 3 weeks into RT in these VOIs (p ≥ 0.11, Wilcoxon sign test) allowed us to calculate the repeatability statistics of between-subject means of squares, within-subject means of squares, F-score, and RC. The 2FA method produced RCs in the range of (9.7–11.7)% in gray matter and (12.2–14.5)% in white matter; while the pSR method led to RCs ranging from 10.9 to 17.9% in gray matter and 7.5 to 10.3% in white matter. The overall mean (±SD) RCs produced by the two methods, 12.0 (±1.6)% for 2FA and 12.0 (±3.8)% for pSR, were not significantly different (p = 0.97). A similar repeatability in T1 measurement produced by the time efficient 2FA method compared with the time consuming pSR method demonstrates that the 2FA method is desirable to integrate into dynamic contrast-enhanced MRI for rapid acquisition.

The tissue properties of epicardial and myocardial fat in obesity and Metabolic Syndrome (MetS) are poorly understood. The purpose of this study is to evaluate cardiac function and quantify fat deposition in MetS using functional and multi-echo Dixon (mDixon) cardiac magnetic resonance imaging (MRI). Eight subjects were imaged in this prospective study. The subjects with MetS had larger epicardial fat volume, higher epicardial percent (%) fat, lower epicardial water to fat ratio (WFR), and higher ratio between epicardial and subcutaneous %fat than the healthy subjects. The obese subjects without MetS and subjects with MetS had similar epicardial %fat in the epicardial and subcutaneous fat depots. Unlike the MetS subjects, the healthy subjects had different %fat in the subcutaneous and epicardial fat depots. In conclusion, this study demonstrates the feasibility of acquiring clinically diagnostic mDixon images for generating MR-based imaging signatures of obesity phenotypes in MetS.

Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kep vs. 0.74 for Ktrans), suggesting that it might be a more robust imaging biomarker of prostate microvasculature than Ktrans.

Myelofibrosis (MF) is a hematologic neoplasm arising as a primary disease or secondary to other myeloproliferative neoplasms (MPNs). Both primary and secondary MF are uniquely associated with progressive bone marrow fibrosis, displacing normal hematopoietic cells from the marrow space and disrupting normal production of mature blood cells. Activation of the JAK2 signaling pathway in hematopoietic stem cells commonly causes MF, and ruxolitinib, a drug targeting this pathway, is the treatment of choice for many patients. However, current measures of disease status in MF do not necessarily predict response to treatment with ruxolitinib or other drugs in MF. Bone marrow biopsies are invasive and prone to sampling error, while measurements of spleen volume only indirectly reflect bone marrow status. Toward the goal of developing an imaging biomarker for treatment response in MF, we present preliminary results from a prospective clinical study evaluating parametric response mapping (PRM) of quantitative Dixon MRI bone marrow fat fraction maps in four MF patients treated with ruxolitinib. PRM allows for the voxel-wise identification of significant change in quantitative imaging readouts over time, in this case the bone marrow fat content. We identified heterogeneous response patterns of bone marrow fat among patients and within different bone marrow sites in the same patient. We also observed discordance between changes in bone marrow fat fraction and reductions in spleen volume, the standard imaging metric for treatment efficacy. This study provides initial support for PRM analysis of quantitative MRI of bone marrow fat to monitor response to therapy in MF, setting the stage for larger studies to further develop and validate this method as a complementary imaging biomarker for this disease.

Spatially nonuniform diffusion weighting bias as a result of gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from the magnet isocenter. Our previously described approach effectively removed spatial ADC bias from 3 orthogonal diffusion-weighted imaging (DWI) measurements for monoexponential media of arbitrary anisotropy. This work evaluates correction feasibility and performance for quantitative diffusion parameters of the 2-component intravoxel incoherent motion (IVIM) model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T magnetic resonance imaging scanner near isocenter and offset superiorly. Spatially nonuniform diffusion weighting caused by GNL resulted both in shifting and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to the isocenter. Direction-average diffusion weighting bias correctors were computed based on the known gradient design provided by the vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying precomputed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b maps and DWI intensities in the presence of IVIM perfusion. No significant bias impact was observed for the IVIM perfusion fraction.

Vascular-targeted therapies have shown promise as adjuvant cancer treatment. As these agents undergo clinical evaluation, sensitive imaging biomarkers are needed to assess drug target interaction and treatment response. In this study, dynamic contrast enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DW-MRI) were evaluated for detecting response of intracerebral 9L gliosarcomas to the antivascular agent VEGF-Trap, a fusion protein designed to bind all forms of Vascular Endothelial Growth Factor-A (VEGF-A) and Placental Growth Factor (PGF). Rats with 9L tumors were treated twice weekly for two weeks with vehicle or VEGF-Trap. DCE- and DW-MRI were performed one day prior to treatment initiation and one day following each administered dose. Kinetic parameters (K trans , volume transfer constant; kep ,e fflux rate constant from extravascular/extracellular space to plasma; and vp, blood plasma volume fraction) and the apparent diffusion coefficient (ADC) over the tumor volumes were compared between groups. A significant decrease in kinetic parameters was observed 24 hours following the first dose of VEGF-Trap in treated versus control animals (p

Objective: In a recent multi-center trial of gadolinium contrast-enhanced magnetic resonance angiography (Gd-MRA) for diagnosis of acute pulmonary embolism (PE), two centers utilized a common MRI platform though at different field strengths (1.5T and 3T) and realized a signal-to-noise gain with the 3T platform. This retrospective analysis investigates this gain in signal-to-noise of pulmonary vascular targets. Methods: Thirty consecutive pulmonary MRA examinations acquired on a 1.5T system at one institution were compared to 30 consecutive pulmonary MRA examinations acquired on a 3T system at a different institution. Both systems were from the same MRI manufacturer and both used the same Gd-MRA pulse sequence, although there were some protocol adjustments made due to field strength differences. Region-of-interests were manually defined on the main pulmonary artery, 4 pulmonary veins, thoracic aorta, and background lung for objective measurement of signal-to-noise, contrast-to-noise, and bolus timing bias between centers. Results: The 3T pulmonary MRA protocol achieved higher spatial resolution yet maintained significantly higher signal-to-noise ratio (≥13%, p = 0.03) in the main pulmonary vessels relative to 1.5T. There was no evidence of operator bias in bolus timing or patient hemodynamic differences between groups. Conclusion: Relative to 1.5T, higher spatial resolution Gd-MRA can be achieved at 3T with a sustained or greater signal-to-noise ratio of enhanced vasculature.

Purpose: Currently, radiologic response of brain tumors is assessed according to the Macdonald criteria 10 weeks from the start of therapy. There exists a critical need to identify nonresponding patients early in the course of their therapy for consideration of alternative treatment strategies. Our study assessed the effectiveness of the parametric response map (PRM) imaging biomarker to provide for an earlier measure of patient survival prediction. Experimental Design: Forty-five high-grade glioma patients received concurrent chemoradiation. Quantitative MRI including apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) maps were acquired pretreatment and 3 weeks midtreatment on a prospective institutional-approved study. PRM, a voxel-by-voxel image analysis method, was evaluated as an early prognostic biomarker of overall survival. Clinical and conventional MR parameters were also evaluated. Results: Multivariate analysis showed that PRMADC+ in combination with PRMrCBV− obtained at week 3 had a stronger correlation to 1-year and overall survival rates than any baseline clinical or treatment response imaging metric. The composite biomarker identified three distinct patient groups, nonresponders [median survival (MS) of 5.5 months, 95% CI: 4.4–6.6 months], partial responders (MS of 16 months, 95% CI: 8.6–23.4 months), and responders (MS has not yet been reached). Conclusions: Inclusion of PRMADC+ and PRMrCBV− into a single imaging biomarker metric provided early identification of patients resistant to standard chemoradiation. In comparison to the current standard of assessment of response at 10 weeks (Macdonald criteria), the composite PRM biomarker potentially provides a useful opportunity for clinicians to identify patients who may benefit from alternative treatment strategies. Clin Cancer Res; 17(14); 4751–60. ©2011 AACR.

The aim of this study was to empirically test the effect of chemotherapy-induced tissue changes in a glioma model as measured by several diffusion indices calculated from nonmonoexponential formalisms over a wide range of b-values. We also compared these results to the conventional two-point apparent diffusion coefficient calculation using nominal b-values. Diffusion-weighted imaging was performed over an extended range of b-values (120-4000 sec/mm(2) ) on intracerebral rat 9L gliomas before and after a single dose of 1,3-bis(2-chloroethyl)-1-nitrosourea. Diffusion indices from three formalisms of diffusion-weighted signal decay [(a) two-point analytical calculation using either low or high b-values, (b) a stretched exponential formalism, and (c) a biexponential fit] were tested for responsiveness to therapy-induced differences between control and treated groups. Diffusion indices sensitive to "fast diffusion" produced the largest response to treatment, which resulted in significant differences between groups. These trends were not observed for "slow diffusion" indices. Although the highest rate of response was observed from the biexponential formalism, this was not found to be significantly different from the conventional monoexponential apparent diffusion coefficient method. In conclusion, parameters from the more complicated nonmonoexponential formalisms did not provide additional sensitivity to treatment response in this glioma model beyond that observed from the two-point conventional monoexponential apparent diffusion coefficient method.

(18)F-FDG PET is an established functional imaging modality for the evaluation of human disease. Diffusion-weighted MRI (DWI) is another rapidly evolving functional imaging modality that can be used to evaluate oncologic and nononcologic lesions throughout the body. The information provided by (18)F-FDG PET and DWI can be complementary, because the 2 methods are based on completely different biophysical underpinnings. This article will describe the basic principles, clinical applications, and limitations of DWI. In addition, the available evidence that correlates and compares (18)F-FDG PET and DWI will be reviewed.

Purpose: In a phase I study, the combination of gemcitabine and imatinib was well tolerated with broad anticancer activity. This phase I trial evaluated the triplet of docetaxel, gemcitabine and imatinib. Experimental Design: Imatinib was administered at 400 mg daily on days 1–5, 8–12 and 15–19. Gemcitabine was started at 600 mg/m2 at a rate of 10 mg/min on days 3 and 10 and docetaxel at 30 mg/m2 on day 10, on a 21-day cycle. Diffusion and dynamic contrast-enhanced perfusion MRI was performed in selected patients. Results: Twenty patients with relapsed/refractory solid tumors were enrolled in this IRB-approved study. The mean age was 64, and mean ECOG PS was 1. Two patients were evaluated by diffusion/perfusion MRI. After two grade 3 hematological toxicities at dose level 1, the protocol was amended to reduce the dose of imatinib. MTDs were 600 mg/ m2 on days 3 and 10 for gemcitabine, 30 mg/ m2 on day 10 for docetaxel, and 400 mg daily on days 1–5 and 8–12 for imatinib. Dose limiting toxicities after one cycle were neutropenic fever, and pleural and pericardial effusions. The best response achieved was stable disease, for six cycles, in one patient each with mesothelioma and non small cell lung cancer (NSCLC) at the MTD. Two patients with NSCLC had stable disease for four cycles. Discussion: An unexpectedly low MTD for this triplet was identified. Our results suggest drug-drug interactions that amplify toxicities with little evidence of improved tumor control.

Quantifying the amount of brown adipose tissue (BAT) within white adipose tissue (WAT) in human depots may serve as a target to combat obesity. We aimed to quantify proton density fat fraction (PDFF) of BAT and WAT in relatively pure and in mixed preparation using water-fat imaging. Three ex-vivo experiments were performed at 3 T using excised interscapular BAT and inguinal/subcutaneous WAT from mice. The first two experiments consisted of BAT and WAT in separate tubes, and the third used mixed preparation with graded quantities of BAT and WAT. To investigate the influence of partial volume on PDFF metrics, low ( 2.66 mm 3 ) and high spatial resolution ( 0.55 mm 3 acquired voxels) in two orthogonal three-dimensional sections were compared. The low-resolution acquisitions are corrected for T2* and multipeak lipid spectrum, thus considered "quantitative," whereas the high-resolution acquisitions are not corrected but were performed to better spatially segment BAT from WAT zones. As potential BAT metrics, we quantified the average PDFF and the volume of tissue having PDFF ≤ 50 % ( VOL PDFF ≤ 50 % ) based on the PDFF histogram. In the first experiment, the average PDFF of BAT was 23 ± 6 % and 21 ± 7.6 % and the average PDFF of WAT was 76 ± 7 % and 87 ± 7 % using high- and low-resolution techniques, respectively. A similar trend with excellent reproducibility in average PDFF of BAT and WAT was observed in the second experiment. In the third experiment over the four acquisitions, the BAT-dominant tube demonstrated lower PDFF (mean ± SD) of 55 ± 2 % than WAT-dominant ( 69 ± 4 % ) and WAT-only tubes ( 88 ± 4 % ) . Estimating VOL PDFF ≤ 50 % , the BAT-dominant tube demonstrated higher volume of 0.26 cm 3 than WAT-dominant ( 0.16 cm 3 ) and WAT-only tubes ( 0.01 cm 3 ). The presence of BAT exhibits a lower PDFF relative to WAT, thus allowing segmentation of low PDFF tissue for quantification of volume representative of BAT. Future studies will determine the clinical relevance of BAT volume within human depots.

Purpose To assess whether a new method of quantifying therapy-associated hemodynamic alterations may help to distinguish pseudoprogression from true progression in patients with high-grade glioma. Patients and Methods Patients with high-grade glioma received concurrent chemoradiotherapy. Relative cerebral blood volume (rCBV) and blood flow (rCBF) maps were acquired before chemoradiotherapy and at week 3 during treatment on a prospective institutional review board–approved study. Pseudoprogression was defined as imaging changes 1 to 3 months after chemoradiotherapy that mimic tumor progression but stabilized or improved without change in treatment or for which resection revealed radiation effects only. Clinical and conventional magnetic resonance (MR) parameters, including average percent change of rCBV and CBF, were evaluated as potential predictors of pseudoprogression. Parametric response map (PRM), an innovative, voxel-by-voxel method of image analysis, was also performed. Results Median radiation dose was 72 Gy (range, 60 to 78 Gy). Of 27 patients, stable disease/partial response was noted in 13 patients and apparent progression was noted in 14 patients. Adjuvant temozolomide was continued in all patients. Pseudoprogression occurred in six patients. Based on PRM analysis, a significantly reduced blood volume (PRMrCBV) at week 3 was noted in patients with progressive disease as compared with those with pseudoprogression (P < .01). In contrast, change in average percent rCBV or rCBF, MR tumor volume changes, age, extent of resection, and Radiation Therapy Oncology Group recursive partitioning analysis classification did not distinguish progression from pseudoprogression. Conclusion PRMrCBV at week 3 during chemoradiotherapy is a potential early imaging biomarker of response that may be helpful in distinguishing pseudoprogression from true progression in patients with high-grade glioma.

Rationale and Objectives Positron emission tomography (PET) is actively investigated to aid in target volume definition for radiation therapy. The objectives of this study were to apply an automatic computer algorithm to compute target volumes and to validate the algorithm using histologic data from real human prostate cancer. Materials and Methods Various modalities for prostate imaging were performed. In vivo imaging included T2 3-T magnetic resonance imaging and 11C-choline PET. Ex vivo imaging included 3-T magnetic resonance imaging, histology, and block face photos of the prostate specimen. A novel registration method based on mutual information and thin-plate splines was applied to all modalities. Once PET is registered with histology, a voxel-by-voxel comparison between PET and histology is possible. A thresholding technique based on various fractions of the maximum standardized uptake value in the tumor was applied, and the respective computed threshold volume on PET was compared with histologic truth. Results Sixteen patients whose primary tumor volumes ranged from 1.2 to 12.6 cm3 were tested. PET has low spatial resolution, so only tumors > 4 cm3 were considered. Four cases met this criterion. A threshold value of 60% of the 11C-choline maximum standardized uptake value resulted in the highest volume overlap between threshold volume on PET and histology. Medial axis distances between threshold volume on PET and histology showed a mean error of 7.7 ± 5.2 mm. Conclusions This is a proof-of-concept study demonstrating for the first time that histology-guided thresholding on PET can delineate tumor volumes in real human prostate cancer.

Purpose: To compare apparent diffusion coefficients (ADCs) with distributed diffusion coefficients (DDCs) in high-grade gliomas. Materials and Methods: Twenty patients with high-grade gliomas prospectively underwent diffusion-weighted MRI. Traditional ADC maps were created using b-values of 0 and 1000 s/mm2. In addition, DDC maps were created by applying the stretched-exponential model using b-values of 0, 1000, 2000, and 4000 s/mm2. Whole-tumor ADCs and DDCs (in 10−3 mm2/s) were measured and analyzed with a paired t-test, Pearson's correlation coefficient, and the Bland-Altman method. Results: Tumor ADCs (1.14 ± 0.26) were significantly lower (P = 0.0001) than DDCs (1.64 ± 0.71). Tumor ADCs and DDCs were strongly correlated (R = 0.9716; P < 0.0001), but mean bias ± limits of agreement between tumor ADCs and DDCs was −0.50 ± 0.90. There was a clear trend toward greater discordance between ADC and DDC at high ADC values. Conclusion: Under the assumption that the stretched-exponential model provides a more accurate estimate of the average diffusion rate than the mono-exponential model, our results suggest that for a little diffusion attenuation the mono-exponential fit works rather well for quantifying diffusion in high-grade gliomas, whereas it works less well for a greater degree of diffusion attenuation. J. Magn. Reson. Imaging 2010;31:531–537. © 2010 Wiley-Liss, Inc.

Purpose: Functional imaging biomarkers of cancer treatment response offer the potential for early determination of outcome through the assessment of biochemical, physiologic, and microenvironmental readouts. Cell death may result in an immunologic response, thus complicating the interpretation of biomarker readouts. This study evaluated the temporal effect of treatment-associated inflammatory activity on diffusion magnetic resonance imaging and 2-[18F]-fluoro-2-deoxy-d-glucose-positron emission tomography imaging (FDG-PET) biomarkers to delineate the effects of the inflammatory response on imaging readouts. Experimental Design: Rats with intracerebral 9L gliosarcomas were separated into four groups consisting of control, an immunosuppressive agent dexamethasone (Dex), 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU), and BCNU+Dex. Animals were imaged using diffusion-weighted magnetic resonance imaging and FDG-PET at 0, 3, and 7 days posttreatment. Results: In the BCNU- and BCNU+Dex-treated animal groups, diffusion values increased progressively over the 7-day study period to ∼23% over baseline. The FDG percentage change of standard uptake value decreased at day 3 (−30.9%) but increased over baseline levels at day 7 (+20.1%). FDG-PET of BCNU+Dex-treated animals were found to have percentage of standard uptake value reductions of −31.4% and −24.7% at days 3 and 7, respectively, following treatment. Activated macrophages were observed on day 7 in the BCNU treatment group with much fewer found in the BCNU+Dex group. Conclusions: Results revealed that treatment-associated inflammatory response following tumor therapy resulted in the accentuation of tumor diffusion response along with a corresponding increase in tumor FDG uptake due to the presence of glucose-consuming activated macrophages. The dynamics and magnitude of potential inflammatory response should be considered when interpreting imaging biomarker results. Clin Cancer Res; 16(5); 1542–52

BACKGROUND AND PURPOSE: Does the K-means algorithm do a better job of differentiating benign and malignant neck pathologies compared to only mean ADC? The objective of our study was to analyze the differences between ADC partitions to evaluate whether the K-means technique can be of additional benefit to whole-lesion mean ADC alone in distinguishing benign and malignant neck pathologies. MATERIAL AND METHODS: MR imaging studies of 10 benign and 10 malignant proved neck pathologies were postprocessed on a PC by using in-house software developed in Matlab. Two neuroradiologists manually contoured the lesions, with the ADC values within each lesion clustered into 2 (low, ADC-ADCL; high, ADC-ADCH) and 3 partitions (ADCL; intermediate, ADC-ADCI; ADCH) by using the K-means clustering algorithm. An unpaired 2-tailed Student t test was performed for all metrics to determine statistical differences in the means of the benign and malignant pathologies. RESULTS: A statistically significant difference between the mean ADCL clusters in benign and malignant pathologies was seen in the 3-cluster models of both readers (P = .03 and .022, respectively) and the 2-cluster model of reader 2 (P = .04), with the other metrics (ADCH, ADCI; whole-lesion mean ADC) not revealing any significant differences. ROC curves demonstrated the quantitative differences in mean ADCH and ADCL in both the 2- and 3-cluster models to be predictive of malignancy (2 clusters: P = .008, area under curve = 0.850; 3 clusters: P = .01, area under curve = 0.825). CONCLUSIONS: The K-means clustering algorithm that generates partitions of large datasets may provide a better characterization of neck pathologies and may be of additional benefit in distinguishing benign and malignant neck pathologies compared with whole-lesion mean ADC alone.

Advanced imaging provides insight into biophysical, physiologic, metabolic, or functional properties of tissues. Since water mobility is sensitive to cellular homeostasis, cellular density and microstructural organization, it is considered a valuable tool in the advanced imaging arsenal. This article briefly summarizes diffusion imaging concepts and highlights clinical applications of diffusion MRI for oncologic imaging. The inverse relationship between water mobility and density of cellular elements has been exploited in attempts to characterize and grade brain tumor based on apparent diffusion coefficient (ADC), as well as distinguish tumor from peritumoral edema. Diffusion tensor imaging and its derivative maps of diffusion anisotropy allow assessment of tumor compression or destruction of adjacent normal tissue anisotropy thus may aid to assess tumor infiltration and aid pre-surgical planning. A variety of preclinical studies on treated tumor models demonstrate ADC is sensitive to therapeutic alteration of tumor by effective cytotoxic agents, and that ADC changes are measurable before the lesion shrinks in size. In corresponding clinical studies, these ADC changes have been detected before completion of fractionated chemo-radiation schedules thus diffusion-based biomarkers of response have the potential to be used to intervene and individualize therapy delivery. Several methods to distill diffusion information into quantitative biomarkers have been proposed and include tumor summary statistics of baseline ADC/FA values and their change with time, as well as production of voxel-by-voxel response maps that reflect the relative volume of responding tumor. The voxel-based methods require coregistration of image volumes but this approach may also have value to guide spatially-directed therapies.

The goal of this study was to develop an automated method to segment breast masses on dynamic contrast-enhanced (DCE) magnetic resonance (MR) scans and to evaluate its potential for estimating tumor volume on pre- and postchemotherapy images and tumor change in response to treatment. A radiologist experienced in interpreting breast MR scans defined a cuboid volume of interest (VOI) enclosing the mass in the MR volume at one time point within the sequence of DCE-MR scans. The corresponding VOIs over the entire time sequence were then automatically extracted. A new 3D VOI representing the local pharmacokinetic activities in the VOI was generated from the 4D VOI sequence by summarizing the temporal intensity enhancement curve of each voxel with its standard deviation. The method then used the fuzzy c-means (FCM) clustering algorithm followed by morphological filtering for initial mass segmentation. The initial segmentation was refined by the 3D level set (LS) method. The velocity field of the LS method was formulated in terms of the mean curvature which guaranteed the smoothness of the surface, the Sobel edge information which attracted the zero LS to the desired mass margin, and the FCM membership function which improved segmentation accuracy. The method was evaluated on 50 DCE-MR scans of 25 patients who underwent neoadjuvant chemotherapy. Each patient had pre- and postchemotherapy DCE-MR scans on a 1.5 T magnet. The in-plane pixel size ranged from 0.546 to 0.703 mm and the slice thickness ranged from 2.5 to 4.5 mm. The flip angle was 15 degrees, repetition time ranged from 5.98 to 6.7 ms, and echo time ranged from 1.2 to 1.3 ms. Computer segmentation was applied to the coronal T1-weighted images. For comparison, the same radiologist who marked the VOI also manually segmented the mass on each slice. The performance of the automated method was quantified using an overlap measure, defined as the ratio of the intersection of the computer and the manual segmentation volumes to the manual segmentation volume. Pre- and postchemotherapy masses had overlap measures of 0.81 +/- 0.13 (mean +/- s.d.) and 0.71 +/- 0.22, respectively. The percentage volume reduction (PVR) estimated by computer and the radiologist were 55.5 +/- 43.0% (mean +/- s.d.) and 57.8 +/- 51.3%, respectively. Paired Student's t test indicated that the difference between the mean PVRs estimated by computer and the radiologist did not reach statistical significance (p = 0.641). The automated mass segmentation method may have the potential to assist physicians in monitoring volume change in breast masses in response to treatment.

Purpose Our current understanding of intrafraction pancreatic tumor motion due to respiration is limited. In this study, we characterized pancreatic tumor motion and evaluated the application of several radiotherapy motion management strategies. Methods and Materials Seventeen patients with unresectable pancreatic cancer were enrolled in a prospective internal review board–approved study and imaged during shallow free-breathing using cine MRI on a 3T scanner. Tumor borders were agreed on by a radiation oncologist and an abdominal MRI radiologist. Tumor motion and correlation with the potential surrogates of the diaphragm and abdominal wall were assessed. These data were also used to evaluate planning target volume margin construction, respiratory gating, and four-dimensional treatment planning for pancreatic tumors. Results Tumor borders moved much more than expected. To provide 99% geometric coverage, margins of 20 mm inferiorly, 10 mm anteriorly, 7 mm superiorly, and 4 mm posteriorly are required. Tumor position correlated poorly with diaphragm and abdominal wall position, with patient-level Pearson correlation coefficients of –0.18–0.43. Sensitivity and specificity of gating with these surrogates was also poor, at 53%–68%, with overall error of 35%–38%, suggesting that the tumor may be underdosed and normal tissues overdosed. Conclusions Motion of pancreatic tumor borders is highly variable between patients and larger than expected. There is substantial deformation with breathing, and tumor border position does not correlate well with abdominal wall or diaphragmatic position. Current motion management strategies may not account fully for tumor motion and should be used with caution.

Metastatic prostate cancer continues to be the second leading cause of cancer death in American men with an estimated 28,660 deaths in 2008. Recently, monocyte chemoattractant protein-1 (MCP-1, CCL2) has been identified as an important factor in the regulation of prostate metastasis. CCL2, shown to attract macrophages to the tumor site, has a direct promotional effect on tumor cell proliferation, migration, and survival. Previous studies have shown that anti-CCL2 antibodies given in combination with docetaxel were able to induce tumor regression in a pre-clinical prostate cancer model. A limitation for evaluating new treatments for metastatic prostate cancer to bone is the inability of imaging to objectively assess response to treatment. Diffusion-weighted MRI (DW-MRI) assesses response to anticancer therapies by quantifying the random (i.e., Brownian) motion of water molecules within the tumor mass, thus identifying cells undergoing apoptosis. We sought to measure the treatment response of prostate cancer in an osseous site to docetaxel, an anti-CCL2 agent, and combination treatments using DW-MRI. Measurements of tumor apparent diffusion coefficient (ADC) values were accomplished over time during a 14-day treatment period and compared to response as measured by bioluminescence imaging and survival studies. The diffusion data provided early predictive evidence of the most effective therapy, with survival data results correlating with the DW-MRI findings. DW-MRI is under active investigation in the pre-clinical and clinical settings to provide a sensitive and quantifiable means for early assessment of cancer treatment outcome.

Four-dimensional time-resolved MR angiography (4D-MRA) using keyhole imaging techniques is a new method of performing contrastenhanced vascular imaging. Combining parallel imaging and keyhole imaging techniques, it is possible to obtain dynamic MRA scans up to 60 times faster, thereby achieving subsecond sampling of the contrast hemodynamics. Furthermore, imaging at 3 T gives higher signal, thus affording higher spatial resolution and allowing dynamic 3D MRA to approach the diagnostic performance of conventional digital subtraction angiography. This article presents the authors' clinical experience using 4D-MRA to evaluate various vascular abnormalities in the brain, spine, orbits, and neck at 3 T, demonstrates the imaging findings of this novel technique, and discusses its advantages and use in current neuroradiology practice.

Magnetic resonance provides a wide variety of possibilities for arterial and venous blood vessel imaging in all vascular territories. This article provides a brief review of the technical principles of MR angiography. The first section is dedicated to non-contrast-enhanced angiography techniques and includes several distinct approaches: time-of-flight, phase contrast, triggered angiography non-contrast-enhanced, and balanced steady-state free precession. The second section relates to the contrast-enhanced and time-resolved contrast-enhanced MR angiography methods. The latest technical developments in MR imaging hardware, sequences and software, coil technology, and reconstruction capability allow dynamic MR angiography performance similar to CT angiography, without risks of iodine contrast agent and ionizing radiation exposure.

For the treatment of squamous cell cancer of the head and neck (SCCHN), the assessment of treatment response is traditionally accomplished by volumetric measurements and has been suggested to be prognostic for an eventual response to treatment. An early evaluation response during the course of radiation therapy could provide an opportunity to tailor treatment to individual patients. Diffusion magnetic resonance imaging (MRI) allows for the quantification of tissue water diffusion values, thus treatment-induced loss of tumor cells will result in the increase in water mobility at the microscopic level, which can be detected as an increase in tumor diffusion values before any volumetric changes occur. We evaluated the use of diffusion MRI as an imaging biomarker of treatment response in an orthotopic mouse model of SCCHN. Mice with murine squamous cells expressing the yeast transgene cytosine deaminase were treated with 5-fluorocytosine (5FC), ionizing radiation, and combined therapy and were compared with control animals both during and after treatment for changes in tumor volumes, diffusion values, and survival. Radiation therapy had minimal effect on volumetric growth rate, diffusion, or survival. Although 5FC and combination treatment resulted in similar reductions in tumor volumes, the combination treatment elicited a much greater increase in tumor diffusion values, which correlated with improved survival. Thus, diffusion MRI as an imaging biomarker has a potential for early evaluation of the response to chemoradiation treatment in SCCHN.

Rationale and Objectives Registration enables quantitative spatial correlation of features from different imaging modalities. Our objective is to register in vivo imaging with histologic sections of the human prostate so that histologic truth can be correlated with in vivo imaging features. Materials and Methods In vivo imaging of the prostate included T2-weighted anatomic and diffusion weighted 3-T magnetic resonance imaging (MRI) as well as 11 C-choline positron emission tomography (PET). In addition, ex vivo 3-T MRI of the prostate specimen, histology, and associated block face photos of the prostate specimen were obtained. A standard registration method based on mutual information (MI) and thin-plate spline (TPS) was applied. Registration among in vivo imaging modalities is well established; however, accurate registration involving histology is difficult. Our approach breaks up the difficult direct registration of histology and in vivo imaging into achievable subregistration tasks involving intermediate ex vivo modalities like block face photography and specimen MRI. Results of subregistration tasks are combined to compute the intended, final registration between in vivo imaging and histology. Results The methodology was applied to two patients and found to be clinically feasible. Overall registered anatomic MRI, diffusion MRI, and 11 C-choline PET aligned well with histology qualitatively for both patients. There is no ground truth of registration accuracy as the scans are real patient scans. An indirect validation of the registration accuracy has been proposed comparing tumor boundary markings found in diffusion MRI and histologic sections. Registration errors for two patients between diffusion MRI and histology were 3.74 and 2.26 mm. Conclusion This proof of concept paper demonstrates a method based on intrinsic image information content for successfully registering in vivo imaging of the human prostate with its post-resection histology, which does not require the use of extrinsic fiducial markers. The methodology successfully mapped histology onto the in vivo imaging space, allowing the observation of how well different in vivo imaging features correspond to histologic truth. The methodology is therefore the basis for a systematic comparison of in vivo imaging for staging of human prostate cancer.

The state of the art of diagnostic evaluation of hemodynamically stable patients with suspected acute pulmonary embolism was reviewed. Diagnostic evaluation should begin with clinical assessment using a validated prediction rule in combination with measurement of D-dimer when appropriate. Imaging should follow only when necessary. Although with 4-slice computed tomography (CT) and 16-slice CT, the sensitivity for detection of pulmonary embolism was increased by combining CT angiography with CT venography, it is not known whether CT venography increases the sensitivity of 64-slice CT angiography. Methods to reduce the radiation exposure of CT venography include imaging only the proximal leg veins (excluding the pelvis) and obtaining discontinuous images. Compression ultrasound can be used instead. In young women, radiation of the breasts produces the greatest risk of radiation-induced cancer. It may be that scintigraphy is the imaging test of choice in such patients, but this pathway should be tested prospectively. A patient-specific approach to the diagnosis of pulmonary embolism can be taken safely in hemodynamically stable patients to increase efficiency and decrease cost and exposure to radiation.

To quantify the radiation-induced changes in normal-appearing white matter before, during, and after radiotherapy (RT) in cerebral tumor patients.Twenty-five patients with low-grade glioma, high-grade glioma, or benign tumor treated with RT were studied using diffusion tensor magnetic resonance imaging. The biologically corrected doses ranged from 50 to 81 Gy. The temporal changes were assessed before, during, and to 45 weeks after the start of RT. The mean diffusivity of water (D), fractional anisotropy of diffusion, diffusivity perpendicular (lambdaperpendicular) and parallel (lambda||) to white matter fibers were calculated in normal-appearing genu and splenium of the corpus callosum.In the genu and splenium, fractional anisotropy decreased andD, lambda||, lambdaperpendicular increased linearly and significantly with time (p0.01). At 45 weeks after the start of RT, lambdaperpendicular had increased approximately 30% in the genu and splenium, and lambda|| had increased 5% in the genu and 9% in the splenium, suggesting that demyelination is predominant. The increases in lambdaperpendicular and lambda|| were dose dependent, starting at 3 weeks and continuing to 32 weeks from the start of RT. The dose-dependent increase in lambdaperpendicular and lambda|| was not sustained after 32 weeks, indicating the transition from focal to diffuse effects.The acute and subacute changes in normal-appearing white matter fibers indicate radiation-induced demyelination and mild structural degradation of axonal fibers. The structural changes after RT are progressive, with early dose-dependent demyelination and subsequent diffuse dose-independent demyelination and mild axonal degradation. Diffusion tensor magnetic resonance imaging is potentially a biomarker for the assessment of radiation-induced white matter injury.

Thermal strain imaging (TSI) is demonstrated in two model systems mimicking two potential clinical applications. First, a custom ultrasound (US) microscope produced high-resolution TSI images of an excised porcine coronary artery. Samples were placed in a temperature-controlled water chamber and scanned transversely and longitudinally. Phase-sensitive, correlation-based speckle tracking was applied to map the spatial distribution of temporal strain across the sample. TSI differentiated fatty tissue from water-based arterial wall and muscle with high contrast and a spatial resolution of 60 microm for a 50-MHz transducer. Both transverse and longitudinal TSI images compared well with B-scans of arterial wall structures, including intima, media, adventitia, and overlying fatty tissue. A second model system was used to test the hypothesis that US can produce the heating pattern required for TSI of internal structures. A 2-D phased array with independent drive electronics was combined with a conventional US scanner (iU22, Philips, Bothell, WA) for these studies. This 513-element array, originally designed for the US therapy, acted as the US heat source. To quantify the temporal strain induced by this system, TSI was performed on a homogeneous rubber phantom. TSI temperature estimates were within 3% error for a 3.2 degrees C temperature rise produced within 2 s using a specially designed beamformer and pulse sequencer. The system was then used to produce TSI scanning of an excised kidney containing an intact piece of fat below the collecting system. These images were validated using an magnetic resonance imaging (MRI) pulse sequence designed for lipid quantification. TSI scans matched well MRI scans and histology both anatomically and quantitatively. Finally, to test the potential of US-induced TSI for a significant clinical problem, images were obtained on an excised canine aorta with fatty tissue inside the lumen. Both longitudinal and transversal TSI agreed well with anatomy. These in vitro results demonstrate the potential of high-resolution US-induced TSI with a small temperature change (1 degrees C) for plaque characterization.

A simple phase error correction technique used for field map estimation with a generally available dual-echo gradient-echo (GRE) sequence is presented. Magnetic field inhomogeneity maps estimated using two separate GRE volume acquisitions at different echo times are prone to dynamic motion errors between acquisitions. By using the dual-echo sequence, the data are collected during two back-to-back readout gradients in opposite polarity after a single radio frequency pulse, and interecho motion artifacts and alignment errors in field map estimation can be factored out. Residual phase error from the asymmetric readout pulses is modeled as an affine term in the readout direction. Results from phantom and human data suggest that the first-order phase correction term stays constant over time and, hence, can be applied to different data acquired with the same protocol over time. The zero-order phase correction term may change with time and is estimated empirically for different scans.

Prostate cancer ranks as the most common lethal malignancy diagnosed and the second leading cause of cancer mortality in American men. Although high response rates are achieved using androgen blockade as first-line therapy, most men progress toward hormone-refractory prostate cancer. Systemic chemotherapies have been shown to improve clinical outcome in hormone refractory prostate cancer patients; however, they are not curative. Due to the high incidence of bone involvement in hormone-refractory prostate cancer, assessment of treatment response in metastatic prostate cancer to the bone remains a major clinical need. In this current study, we investigated the feasibility of using the functional diffusion map (fDM) as an imaging biomarker for assessing early treatment response in a preclinical model of metastatic prostate cancer. The fDM biomarker requires a pretreatment and midtreatment magnetic resonance imaging diffusion map, which is used to quantify spatially distinct therapeutic-induced changes in the Brownian motion (or diffusion) of water within tumor tissue. Because water within tumor cells is in a restricted environment relative to extracellular water, loss of cell membrane integrity and cellular density during therapy will be detected by fDM as an increase in diffusion. Regions of significantly increased diffusion values were detected early using fDM in docetaxel-treated versus untreated metastatic prostate bone tumors at 7 days post treatment initiation (P < 0.05), indicating loss of tumor cell viability. Validation of fDM results was accomplished by histologic analysis of excised tissue. Results from this study show the capability of fDM as a biomarker for detection of bone cancer treatment efficacy, thus warranting clinical evaluation. [Cancer Res 2007;67(8):3524–8]