The standard pharmacokinetic model for the analysis of MRI contrast reagent (CR) bolus-tracking (B-T) data assumes that the mean intracellular water molecule lifetime (tau(i)) is effectively zero. This assertion is inconsistent with a considerable body of physiological measurements. Furthermore, theory and simulation show the B-T time-course shape to be very sensitive to the tau(i) magnitude in the physiological range (hundreds of milliseconds to several seconds). Consequently, this standard model aspect can cause significant underestimations (factors of 2 or 3) of the two parameters usually determined: K(trans), the vascular wall CR transfer rate constant, and v(e), the CR distribution volume (the extracellular, extravascular space fraction). Analyses of animal model data confirmed two predicted behaviors indicative of this standard model inadequacy: (1) a specific temporal pattern for the mismatch between the best-fitted curve and data; and (2) an inverse dependence of the curve's K(trans) and v(e) magnitudes on the CR dose. These parameters should be CR dose-independent. The most parsimonious analysis allowing for realistic tau(i) values is the 'shutter-speed' model. Its application to the experimental animal data essentially eliminated the two standard model signature inadequacies. This paper reports the first survey for the extent of this 'shutter-speed effect' in human data. Retrospective analyses are made of clinical data chosen from a range of pathology (the active multiple sclerosis lesion, the invasive ductal carcinoma breast tumor, and osteosarcoma in the leg) that provides a wide variation, particularly of K(trans). The signature temporal mismatch of the standard model is observed in all cases, and is essentially eliminated by use of the shutter-speed model. Pixel-by-pixel maps show that parameter values from the shutter-speed analysis are increased by more than a factor of 3 for some lesion regions. This endows the lesions with very high contrast, and reveals heterogeneities that are often not seen in the standard model maps. Normal muscle regions in the leg allow validation of the shutter-speed model K(trans), v(e), and tau(i) magnitudes, by comparison with results of previous careful rat leg studies not possible for human subjects.

Purpose Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. Methods Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ±150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients and eddy currents were assessed independently. The observed bias errors were compared to numerical models. Results The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between −55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (±5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image co-registration of individual gradient directions. Conclusion The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies.

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.

The standard pharmacokinetic model applied to contrast reagent (CR) bolus-tracking (B-T) MRI (dynamic-contrast-enhanced) data makes the intrinsic assumption that equilibrium transcytolemmal water molecule exchange is effectively infinitely fast. Theory and simulation have suggested that this assumption can lead to significant errors. Recent analyses of animal model experimental data have confirmed two predicted signature inadequacies: a specific temporal mismatch with the B-T time-course and a CR dose-dependent underestimation of model parameters. The most parsimonious adjustment to account for this aspect leads to the "shutter-speed" pharmacokinetic model. Application of the latter to the animal model data mostly eliminates the two signature inadequacies. Here, the standard and shutter-speed models are applied to B-T data obtained from routine human breast examinations. The MRI contrast reagent (CR) bolus-tracking (B-T) (also called dynamic-contrast-enhanced)] method holds great promise for quantitative in vivo evaluation of vascular properties under many different pathophysiological conditions (1). An area that has seen considerable such activity is breast disease (2-5). The many pharmacokinetic models applied to CR B-T data can be divided into two families; one in which the CR and H 2 O are assumed uniformly distributed within each compartment entered ["well-mixed," e.g., (1)] and one in which they are not ["heterogeneous," surveyed in (6)]. For a given number of compartments, the former models have fewer variable parameters: heterogeneous distributions require geometric quantities. Of course, for a given model family, the number of parameters increases with the number of compartments. Even the simplest well-mixed model, which considers only two compartments for CR (1), has seven potential parameters (listed below) (7). Most fittings employ versions in which only two of these, K trans [a pseudo-firstorder rate constant for CR transfer between blood plasma and extracellular, extravascular space (EES)] and the CR distribution volume, equated to v e (the EES volume fraction)-or combinations thereof-are varied (1). However, we have recently shown that this "standard model" embeds the intrinsic assumption that an important eighth parameter, the mean intracellular water lifetime ( i ), is effectively zero: that is, the equilibrium transcytolemmal water exchange system is constrained to the fast-exchangelimit (FXL) (7). This is inconsistent with cytolemmal water permeability coefficient (P) values (measured over many years), which when combined with mean cell sizes allow calculations of i [ϭ r/(3P), for a sphere of radius r]: this is reviewed in Ref. (8). These estimates, along with recent independent measurements (8 -11), yield i values that for almost all cells (except erythrocytes) range from hundreds of milliseconds to several seconds. Such magnitudes have significant effects on the two-compartment model B-T time-course amplitude and shape, causing data fitting with the standard model to underestimate the K tran...

The purpose is to compare quantitative dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) metrics with imaging tumor size for early prediction of breast cancer response to neoadjuvant chemotherapy (NACT) and evaluation of residual cancer burden (RCB). Twenty-eight patients with 29 primary breast tumors underwent DCE-MRI exams before, after one cycle of, at midpoint of, and after NACT. MRI tumor size in the longest diameter (LD) was measured according to the RECIST (Response Evaluation Criteria In Solid Tumors) guidelines. Pharmacokinetic analyses of DCE-MRI data were performed with the standard Tofts and Shutter-Speed models (TM and SSM). After one NACT cycle the percent changes of DCE-MRI parameters Ktrans (contrast agent plasma/interstitium transfer rate constant), ve (extravascular and extracellular volume fraction), kep (intravasation rate constant), and SSM-unique τi (mean intracellular water lifetime) are good to excellent early predictors of pathologic complete response (pCR) vs. non-pCR, with univariate logistic regression C statistics value in the range of 0.804 to 0.967. ve values after one cycle and at NACT midpoint are also good predictors of response, with C ranging 0.845 to 0.897. However, RECIST LD changes are poor predictors with C = 0.609 and 0.673, respectively. Post-NACT Ktrans, τi, and RECIST LD show statistically significant (P < .05) correlations with RCB. The performances of TM and SSM analyses for early prediction of response and RCB evaluation are comparable. In conclusion, quantitative DCE-MRI parameters are superior to imaging tumor size for early prediction of therapy response. Both TM and SSM analyses are effective for therapy response evaluation. However, the τi parameter derived only with SSM analysis allows the unique opportunity to potentially quantify therapy-induced changes in tumor energetic metabolism.

The VFA protocols with 2 to 3 flip angles optimized for different applications achieved acceptable balance of extensive spatial coverage, accuracy, and repeatability in T quantification (errors < 15%). Further optimization in terms of flip-angle choice for each tissue application, and the use of B correction, are needed to improve the robustness of VFA protocols for T mapping. Magn Reson Med 79:2564-2575, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Purpose The maternal microvasculature of the primate placenta is organized into 10-20 perfusion domains that are functionally optimized to facilitate nutrient exchange to support fetal growth. This study describes a dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) method for identifying vascular domains, and quantifying maternal blood flow in them. Methods A rhesus macaque on the 133rd day of pregnancy (G133, term=165 days) underwent Doppler ultrasound (US) procedures, DCE-MRI, and Cesarean-section delivery. Serial T1-weighted images acquired throughout intravenous injection of a contrast reagent (CR) bolus were analyzed to obtain CR arrival time maps of the placenta. Results Watershed segmentation of the arrival time map identified 16 perfusion domains. The number and location of these domains corresponded to anatomical cotyledonary units observed following delivery. Analysis of the CR wave front through each perfusion domain enabled determination of volumetric flow, which ranged from 9.03 to 44.9 mL/sec (25.2 ± 10.3 mL/sec). These estimates are supported by Doppler US results. Conclusions The DCE-MRI analysis described here provides quantitative estimates of the number of maternal perfusion domains in a primate placenta, and estimates flow within each domain. Anticipated extensions of this technique are to the study placental function in nonhuman primate models of obstetric complications.

This study assessed metabolic functioning of regional brain areas to address whether there is a neurometabolic profile reflecting the underlying neuropathology in individuals with autism spectrum disorders, and if varied profiles correlate with the clinical subtypes. Thirteen children (7-16 years) with autism spectrum disorders and 8 typically developing children were compared on (1)H-magnetic resonance spectroscopy data collected from hippocampus-amygdala and cerebellar regions. The autism spectrum disorder group had significantly lower N-acetyl-aspartate/creatine ratios bilaterally in the hippocampus-amygdala but not cerebellum, whereas myo-inositol/creatine was significantly increased in all measured regions. Choline/creatine was also significantly elevated in the left hippocampus-amygdala and cerebellar regions of children with autism spectrum disorder. Comparisons within the autism spectrum disorder group when clinically subdivided by history of speech delay revealed significant metabolic ratio differences. Magnetic resonance spectroscopy can provide important information regarding abnormal brain metabolism and clinical classification in autism spectrum disorders.