Characterizing the Bone Marrow Environment in Advanced-Stage Myelofibrosis during Ruxolitinib Treatment Using PET/CT and MRI: A Pilot Study.

Current diagnostic criteria for myelofibrosis are largely based on bone marrow (BM) biopsy results. However, these have several limitations, including sampling errors. Explorative studies have indicated that imaging might form an alternative for the evaluation of disease activity, but the heterogeneity in BM abnormalities complicates the choice for the optimal technique. In our prospective diagnostic pilot study, we aimed to visualize all BM abnormalities in myelofibrosis before and during ruxolitinib treatment using both PET/CT and MRI. A random sample of patients was scheduled for examinations at baseline and after 6 and 18 months of treatment, including clinical and laboratory examinations, BM biopsies, MRI (T1-weighted, Dixon, dynamic contrast-enhanced (DCE)) and PET/CT ([15O]water, [18F]NaF)). At baseline, all patients showed low BM fat content (indicated by T1-weighted MRI and Dixon), increased BM blood flow (as measured by [15O]water PET/CT), and increased osteoblastic activity (reflected by increased skeletal [18F]NaF uptake). One patient died after the baseline evaluation. In the others, BM fat content increased to various degrees during treatment. Normalization of BM blood flow (as reflected by [15O]water PET/CT and DCE-MRI) occurred in one patient, who also showed the fastest clinical response. Vertebral [18F]NaF uptake remained stable in all patients. In evaluable cases, histopathological parameters were not accurately reflected by imaging results. A case of sampling error was suspected. We conclude that imaging results can provide information on functional processes and disease distribution throughout the BM. Differences in early treatment responses were especially reflected by T1-weighted MRI. Limitations in the gold standard hampered the evaluation of diagnostic accuracy.

Early Response Prediction of Multiparametric Functional MRI and 18F-FDG-PET in Patients with Head and Neck Squamous Cell Carcinoma Treated with (Chemo)Radiation.

BACKGROUND: Patients with locally-advanced head and neck squamous cell carcinoma (HNSCC) have variable responses to (chemo)radiotherapy. A reliable prediction of outcomes allows for enhancing treatment efficacy and follow-up monitoring. METHODS: Fifty-seven histopathologically-proven HNSCC patients with curative (chemo)radiotherapy were prospectively included. All patients had an MRI (DW,-IVIM, DCE-MRI) and 18F-FDG-PET/CT before and 10 days after start-treatment (intratreatment). Primary tumor functional imaging parameters were extracted. Univariate and multivariate analysis were performed to construct prognostic models and risk stratification for 2 year locoregional recurrence-free survival (LRFFS), distant metastasis-free survival (DMFS) and overall survival (OS). Model performance was measured by the cross-validated area under the receiver operating characteristic curve (AUC). RESULTS: The best LRFFS model contained the pretreatment imaging parameters ADC_kurtosis, Kep and SUV_peak, and intratreatment imaging parameters change (Δ) Δ-ADC_skewness, Δ-f, Δ-SUV_peak and Δ-total lesion glycolysis (TLG) (AUC = 0.81). Clinical parameters did not enhance LRFFS prediction. The best DMFS model contained pretreatment ADC_kurtosis and SUV_peak (AUC = 0.88). The best OS model contained gender, HPV-status, N-stage, pretreatment ADC_skewness, D, f, metabolic-active tumor volume (MATV), SUV_mean and SUV_peak (AUC = 0.82). Risk stratification in high/medium/low risk was significantly prognostic for LRFFS (p = 0.002), DMFS (p < 0.001) and OS (p = 0.003). CONCLUSIONS: Intratreatment functional imaging parameters capture early tumoral changes that only provide prognostic information regarding LRFFS. The best LRFFS model consisted of pretreatment, intratreatment and Δ functional imaging parameters; the DMFS model consisted of only pretreatment functional imaging parameters, and the OS model consisted ofHPV-status, gender and only pretreatment functional imaging parameters. Accurate clinically applicable risk stratification calculators can enable personalized treatment (adaptation) management, early on during treatment, improve counseling and enhance patient-specific post-therapy monitoring.

Repeatability of IVIM biomarkers from diffusion-weighted MRI in head and neck: Bayesian probability versus neural network.

PURPOSE: The intravoxel incoherent motion (IVIM) model for DWI might provide useful biomarkers for disease management in head and neck cancer. This study compared the repeatability of three IVIM fitting methods to the conventional nonlinear least-squares regression: Bayesian probability estimation, a recently introduced neural network approach, IVIM-NET, and a version of the neural network modified to increase consistency, IVIM-NETmod . METHODS: Ten healthy volunteers underwent two imaging sessions of the neck, two weeks apart, with two DWI acquisitions per session. Model parameters (ADC, diffusion coefficient Dt , perfusion fraction fp , and pseudo-diffusion coefficient Dp ) from each fit method were determined in the tonsils and in the pterygoid muscles. Within-subject coefficients of variation (wCV) were calculated to assess repeatability. Training of the neural network was repeated 100 times with random initialization to investigate consistency, quantified by the coefficient of variance. RESULTS: The Bayesian and neural network approaches outperformed nonlinear regression in terms of wCV. Intersession wCV of Dt in the tonsils was 23.4% for nonlinear regression, 9.7% for Bayesian estimation, 9.4% for IVIM-NET, and 11.2% for IVIM-NETmod . However, results from repeated training of the neural network on the same data set showed differences in parameter estimates: The coefficient of variances over the 100 repetitions for IVIM-NET were 15% for both Dt and fp , and 94% for Dp ; for IVIM-NETmod , these values improved to 5%, 9%, and 62%, respectively. CONCLUSION: Repeatabilities from the Bayesian and neural network approaches are superior to that of nonlinear regression for estimating IVIM parameters in the head and neck.

Repeatability of tumor perfusion kinetics from dynamic contrast-enhanced MRI in glioblastoma.

BACKGROUND: Dynamic contrast-enhanced MRI (DCE-MRI) parameters have been shown to be biomarkers for treatment response in glioblastoma (GBM). However, variations in analysis and measurement methodology complicate determination of biological changes measured via DCE. The aim of this study is to quantify DCE-MRI variations attributable to analysis methodology and image quality in GBM patients. METHODS: The Extended Tofts model (eTM) and Leaky Tracer Kinetic Model (LTKM), with manually and automatically segmented vascular input functions (VIFs), were used to calculate perfusion kinetic parameters from 29 GBM patients with double-baseline DCE-MRI data. DCE-MRI images were acquired 2-5 days apart with no change in treatment. Repeatability of kinetic parameters was quantified with Bland-Altman and percent repeatability coefficient (%RC) analysis. RESULTS: The perfusion parameter with the least RC was the plasma volume fraction (v p ), with a %RC of 53%. The extra-cellular extra-vascular volume fraction (v e ) %RC was 82% and 81%, for extended Tofts-Kety Model (eTM) and LTKM respectively. The %RC of the volume transfer rate constant (K trans ) was 72% for the eTM, and 82% for the LTKM, respectively. Using an automatic VIF resulted in smaller %RCs for all model parameters, as compared to manual VIF. CONCLUSIONS: As much as 72% change in K trans (eTM, autoVIF) can be attributable to non-biological changes in the 2-5 days between double-baseline imaging. Poor K trans repeatability may result from inferior temporal resolution and short image acquisition time. This variation suggests DCE-MRI repeatability studies should be performed institutionally, using an automatic VIF method and following quantitative imaging biomarkers alliance guidelines.

Multiparametric functional MRI and 18F-FDG-PET for survival prediction in patients with head and neck squamous cell carcinoma treated with (chemo)radiation.

OBJECTIVES: To assess (I) correlations between diffusion-weighted (DWI), intravoxel incoherent motion (IVIM), dynamic contrast-enhanced (DCE) MRI, and 18F-FDG-PET/CT imaging parameters capturing tumor characteristics and (II) their predictive value of locoregional recurrence-free survival (LRFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy. METHODS: Between 2014 and 2018, patients with histopathologically proven HNSCC, planned for curative (chemo) radiotherapy, were prospectively included. Pretreatment clinical, anatomical, and functional imaging parameters (obtained by DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT) were extracted for primary tumors (PT) and lymph node metastases. Correlations and differences between parameters were assessed. The predictive value of LRFS and OS was assessed, performing univariable, multivariable Cox and CoxBoost regression analyses. RESULTS: In total, 70 patients were included. Significant correlations between 18F-FDG-PET parameters and DWI-/DCE volume parameters were found (r > 0.442, p < 0.002). The combination of HPV (HR = 0.903), intoxications (HR = 1.065), PT ADCGTV (HR = 1.252), Ktrans (HR = 1.223), and Ve (HR = 1.215) was predictive for LRFS (C-index = 0.546; p = 0.023). N-stage (HR = 1.058), HPV positivity (HR = 0.886), hypopharyngeal tumor location (HR = 1.111), ADCGTV (HR = 1.102), ADCmean (HR = 1.137), D* (HR = 0.862), Ktrans (HR = 1.106), Ve (HR = 1.195), SUVmax (HR = 1.094), and TLG (HR = 1.433) were predictive for OS (C-index = 0.664; p = 0.046). CONCLUSIONS: Functional imaging parameters, performing DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT, yielded complementary value in capturing tumor characteristics. More specific, intoxications, HPV-negative status, large tumor volume-related parameters, high permeability (Ktrans), and high extravascular extracellular space (Ve) parameters were predictive for adverse locoregional recurrence-free survival and adverse overall survival. Low cellularity (high ADC) and high metabolism (high SUV) were additionally predictive for decreased overall survival. These different predictive factors added to estimated locoregional and overall survival. KEY POINTS: • Parameters of DWI/IVIM, DCE-MRI, and 18F-FDG-PET/CT were able to capture complementary tumor characteristics. • Multivariable analysis revealed that intoxications, HPV negativity, large tumor volume and high vascular permeability (Ktrans), and extravascular extracellular space (Ve) were complementary predictive for locoregional recurrence. • In addition to predictive parameters for locoregional recurrence, also high cellularity (low ADC) and high metabolism (high SUV) were complementary predictive for overall survival.

Repeatability of arterial input functions and kinetic parameters in muscle obtained by dynamic contrast enhanced MR imaging of the head and neck.

BACKGROUND: Quantification of pharmacokinetic parameters in dynamic contrast enhanced (DCE) MRI is heavily dependent on the arterial input function (AIF). In the present patient study on advanced stage head and neck squamous cell carcinoma (HNSCC) we have acquired DCE-MR images before and during chemo radiotherapy. We determined the repeatability of image-derived AIFs and of the obtained kinetic parameters in muscle and compared the repeatability of muscle kinetic parameters obtained with image-derived AIF's versus a population-based AIF. MATERIALS AND METHODS: We compared image-derived AIFs obtained from the internal carotid, external carotid and vertebral arteries. Pharmacokinetic parameters (ve, Ktrans, kep) in muscle-located outside the radiation area-were obtained using the Tofts model with the image-derived AIFs and a population averaged AIF. Parameter values and repeatability were compared. Repeatability was calculated with the pre- and post-treatment data with the assumption of no DCE-MRI measurable biological changes between the scans. RESULTS: Several parameters describing magnitude and shape of the image-derived AIFs from the different arteries in the head and neck were significantly different. Use of image-derived AIFs led to higher pharmacokinetic parameters compared to use of a population averaged AIF. Median muscle pharmacokinetic parameters values obtained with AIFs in external carotids, internal carotids, vertebral arteries and with a population averaged AIF were respectively: ve (0.65, 0.74, 0.58, 0.32), Ktrans (0.30, 0.21, 0.13, 0.06), kep (0.41, 0.32, 0.24, 0.18). Repeatability of pharmacokinetic parameters was highest when a population averaged AIF was used; however, this repeatability was not significantly different from image-derived AIFs. CONCLUSION: Image-derived AIFs in the neck region showed significant variations in the AIFs obtained from different arteries, and did not improve repeatability of the resulting pharmacokinetic parameters compared with the use of a population averaged AIF. Therefore, use of a population averaged AIF seems to be preferable for pharmacokinetic analysis using DCE-MRI in the head and neck area.

A pharmacokinetic model including arrival time for two inputs and compensating for varying applied flip-angle in dynamic gadoxetic acid-enhanced MR imaging.

PURPOSE: Pharmacokinetic models facilitate assessment of properties of the micro-vascularization based on DCE-MRI data. However, accurate pharmacokinetic modeling in the liver is challenging since it has two vascular inputs and it is subject to large deformation and displacement due to respiration. METHODS: We propose an improved pharmacokinetic model for the liver that (1) analytically models the arrival-time of the contrast agent for both inputs separately; (2) implicitly compensates for signal fluctuations that can be modeled by varying applied flip-angle e.g. due to B1-inhomogeneity. Orton's AIF model is used to analytically represent the vascular input functions. The inputs are independently embedded into the Sourbron model. B1-inhomogeneity-driven variations of flip-angles are accounted for to justify the voxel's displacement with respect to a pre-contrast image. RESULTS: The new model was shown to yield lower root mean square error (RMSE) after fitting the model to all but a minority of voxels compared to Sourbron's approach. Furthermore, it outperformed this existing model in the majority of voxels according to three model-selection criteria. CONCLUSION: Our work primarily targeted to improve pharmacokinetic modeling for DCE-MRI of the liver. However, other types of pharmacokinetic models may also benefit from our approaches, since the techniques are generally applicable.

Evaluation of Dispersion MRI for Improved Prostate Cancer Diagnosis in a Multicenter Study.

OBJECTIVE: The purpose of this study is to compare dispersion MRI and Tofts model (TM) for analysis of quantitative dynamic contrast-enhanced (DCE) MRI (DCE-MRI) for localization of prostate cancer and to assess the correlation between quantitative DCE-MRI parameters and tumor grade. MATERIALS AND METHODS: This retrospective multicenter study included 80 patients with biopsy-proven prostate cancer who underwent DCE-MRI followed by radical prostatectomy. DCE-MRI parameters were extracted from dispersion MRI analysis (the dispersion parameter [kd], the flux rate [kep], and the intravascular mean transit time) and TM analysis (the forward volume transfer constant [Ktrans], kep, and the extravascular extracellular volume fraction [ve]). ROIs representing benign and malignant tissue were drawn on each DCE-MRI slice according to the histopathologic findings, and the diagnostic performance of the estimated parameters for the diagnosis of prostate cancer was evaluated using fivefold cross-validation and ROC curve analysis. Further analysis was conducted for the two most relevant parameters (i.e., kd [for dispersion MRI] and kep [for TM]), to investigate the correlation between DCE-MRI parameters and tumor grade. RESULTS: DCE-MRI parameters were significantly different between benign and malignant prostate tissue (p < 0.0001). The dispersion MRI parameter kd outperformed all other DCE-MRI parameters for prostate cancer diagnosis, showing the highest area under the ROC curve value (p < 0.0001). Only a weak linear correlation (Pearson r = 0.18; p < 0.05) was found between the dispersion parameter and the Gleason grade group. CONCLUSION: Dispersion MRI outperformed TM analysis, improving the diagnostic performance of quantitative DCE-MRI for prostate cancer localization. Of the DCE-MRI parameters, kd (for dispersion MRI) and kep (for TM) provided only poor characterization of tumor grade.

Estimating the arterial input function from dynamic contrast-enhanced MRI data with compensation for flow enhancement (II): Applications in spine diagnostics and assessment of crohn's disease.

BACKGROUND: Pharmacokinetic (PK) models can describe microvascular density and integrity. An essential component of PK models is the arterial input function (AIF) representing the time-dependent concentration of contrast agent (CA) in the blood plasma supplied to a tissue. PURPOSE/HYPOTHESIS: To evaluate a novel method for subject-specific AIF estimation that takes inflow effects into account. STUDY TYPE: Retrospective study. SUBJECTS: Thirteen clinical patients referred for spine-related complaints; 21 patients from a study into luminal Crohn's disease with known Crohn's Disease Endoscopic Index of Severity (CDEIS). FIELD STRENGTH/SEQUENCE: Dynamic fast spoiled gradient echo (FSPGR) at 3T. ASSESSMENT: A population-averaged AIF, AIFs derived from distally placed regions of interest (ROIs), and the new AIF method were applied. Tofts' PK model parameters (including vp and Ktrans ) obtained with the three AIFs were compared. In the Crohn's patients Ktrans was correlated to CDEIS. STATISTICAL TESTS: The median values of the PK model parameters from the three methods were compared using a Mann-Whitney U-test. The associated variances were statistically assessed by the Brown-Forsythe test. Spearman's rank correlation coefficient was computed to test the correlation of Ktrans to CDEIS. RESULTS: The median vp was significantly larger when using the distal ROI approach, compared to the two other methods (P < 0.05 for both comparisons, in both applications). Also, the variances in vp were significantly larger with the ROI approach (P < 0.05 for all comparisons). In the Crohn's disease study, the estimated Ktrans parameter correlated better with the CDEIS (r = 0.733, P < 0.001) when the proposed AIF was used, compared to AIFs from the distal ROI method (r = 0.429, P = 0.067) or the population-averaged AIF (r = 0.567, P = 0.011). DATA CONCLUSION: The proposed method yielded realistic PK model parameters and improved the correlation of the Ktrans parameter with CDEIS, compared to existing approaches. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage 1 J. Magn. Reson. Imaging 2018;47:1197-1204.

Dynamic Contrast-Enhanced Magnetic Resonance Imaging Using Pharmacokinetic Modeling: Initial Experience in Patients With Early Arthritis.

OBJECTIVE: Analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using pharmacokinetic modeling (PKM) provides quantitative measures that mirror microvessel integrity and can be used as an objective marker of the level of synovial inflammation. The aim of this study was to investigate the PKM parameters K(trans) , kep , and ve in a prospective cohort of disease-modifying antirheumatic drug (DMARD)-naive patients with early arthritis, and to validate the results by assessing their correlation with the number of synovial endothelial cells (ECs). METHODS: Forty-seven patients with early arthritis (arthritis duration <1 year, DMARD naive; comprising 14 patients with rheumatoid arthritis, 22 with unclassified arthritis, 6 with spondyloarthritis [SpA], and 5 with other arthritides) were included. At baseline, DCE-MRI was performed on an inflamed knee joint of each patient. These images were used to calculate the K(trans) (volume transfer constant between the plasma and extracellular extravascular space [EES]), the kep (transfer constant between the EES and plasma), and the ve (fractional volume of the EES). Second, markers of disease activity were collected. Finally, vascularity was evaluated by immunohistochemical analysis of synovial tissue samples obtained from the inflamed knee joints, using antibodies to detect von Willebrand factor (vWF), a marker of ECs. RESULTS: The 3 PKM parameters differed significantly between diagnostic groups at baseline, with the highest K(trans) value being observed in patients with SpA (median 0.050/minute, interquartile range [IQR] 0.041- 0.069). Furthermore, the K(trans) , kep , and ve values correlated significantly with markers of disease activity. Finally, the PKM parameters K(trans) and kep , but not ve , correlated significantly with synovial expression of vWF (r = 0.647, P = 0.004 for K(trans) ; r = 0.614, P = 0.007 for kep ; r = 0.398, P = 0.102 for ve ). CONCLUSION: These results suggest that the K(trans) , kep , and ve can be used to detect synovial inflammation in patients with early arthritis, and these PKM parameters may be helpful in differential diagnosis. This approach may also be useful in translational research analyzing tissue microcirculation and angiogenesis.

Simulating the effect of input errors on the accuracy of Tofts' pharmacokinetic model parameters.

Pharmacokinetic modeling in Dynamic Contrast Enhanced (DCE)-MRI is an elegant and useful method that provides valuable insight into angiogenesis in cancer and inflammatory diseases. Despite its widespread use, the reliability of the model results is still questioned, as many factors hamper the calculation of the model's parameters, resulting in the poor reproducibility and accuracy of the method. Pharmacokinetic modeling relies on the knowledge of inputs such as the Arterial Input Function (AIF) and of the tissue contrast agent concentration, both of which are difficult to accurately measure. Any errors in the measurement of either of the inputs propagate into the calculated pharmacokinetic model parameters (PMPs), and the significance of the effect depends on the source of the measurement error. In this work we systematically investigate the effect of the incorrect estimation of the parameters describing the inputs of the model on the calculated PMPs when using Tofts' model. Furthermore, we analyze the dependence of these errors on the native values of the PMPs. We show that errors on the measurement of the native T1 as well as errors on the parameters describing the initial peak of the AIF have the largest impact on the calculated PMPs. The parameter whose error has the least effect is the one describing the slow decay of the AIF. The effect of input parameter (IP) errors on the calculated PMPs is found to be dependent on the native set of PMPs: this is particularly true for the errors in the flip angle, and for the errors in parameters describing the initial AIF peak. Conversely the effect of T1 and AIF scaling errors on the calculated PMPs is only slightly dependent on the native PMPs.

Contrast-enhanced perfusion magnetic resonance imaging for head and neck squamous cell carcinoma: a systematic review.

This systematic review gives an extensive overview of the current state of perfusion-weighted magnetic resonance imaging (MRI) for head and neck squamous cell carcinoma (HNSCC). Pubmed and Embase were searched for literature until July 2014 assessing the diagnostic and prognostic performance of perfusion-weighted MRI in HNSCC. Twenty-one diagnostic and 12 prognostic studies were included for qualitative analysis. Four studies used a T2(∗) sequence for dynamic susceptibility (DSC)-MRI, 29 studies used T1-based sequences for dynamic contrast enhanced (DCE)-MRI. Included studies suffered from a great deal of heterogeneity in study methods showing a wide range of diagnostic and prognostic performance. Therefore we could not perform any useful meta-analysis. Perfusion-weighted MRI shows potential in some aspects of diagnosing HNSCC and predicting prognosis. Three studies reported significant correlations between hypoxia and tumor heterogeneity in perfusion parameters (absolute correlation coefficient |ρ|>0.6, P<0.05). Two studies reported synergy between perfusion-weighted MRI and positron emission tomography (PET) parameters. Four studies showed a promising role for response prediction early after the start of chemoradiotherapy. In two studies perfusion-weighted MRI was useful in the detection of residual disease. However more research with uniform study and analysis protocols with larger sample sizes is needed before perfusion-weighted MRI can be used in clinical practice.

Accuracy of abdominal ultrasound and MRI for detection of Crohn disease and ulcerative colitis in children.

BACKGROUND: Endoscopy is currently the primary diagnostic technique for inflammatory bowel disease (IBD) in children. OBJECTIVE: To assess the accuracy of US and dynamic contrast-enhanced MRI for diagnosing inflammatory bowel disease and for distinguishing Crohn disease and ulcerative colitis in comparison to a reference standard. MATERIALS AND METHODS: Consecutive children with suspected IBD underwent diagnostic workup including ileocolonoscopy and upper gastrointestinal endoscopy as the reference standard, abdominal US, and MR enterography and colonography at 3 T. The protocol included a dynamic contrast-enhanced 3-D sequence. Sensitivity, specificity and kappa values were calculated for one ultrasonographer and two MRI observers. RESULTS: We included 28 children (15 boys) with mean age 14 years (range 10-17 years). The diagnosis was IBD in 23 children (72%), including 12 with Crohn disease, 10 with ulcerative colitis and 1 with indeterminate colitis. For the diagnosis of inflammatory bowel disease the sensitivity was 55% for US and 57% (both observers) for MR entero- and colonography, and the specificity was 100% for US and 100% (observer 1) and 75% (observer 2) for MR entero- and colonography. Combined MRI and US had sensitivity and specificity of 70% and 100% (observer 1) and 74% and 80% (observer 2), respectively. With the addition of a dynamic contrast-enhanced MR sequence, the sensitivity increased to 83% and 87%. US and MRI could only distinguish between Crohn disease and ulcerative colitis when terminal ileum lesions were present. CONCLUSION: US and MR entero- and colonography have a high accuracy for diagnosing inflammatory bowel disease in children but cannot be used to distinguish Crohn disease and ulcerative colitis.

Magnetic resonance dispersion imaging for localization of angiogenesis and cancer growth.

PURPOSE: Cancer angiogenesis can be imaged by using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Pharmacokinetic modeling can be used to assess vascular perfusion and permeability, but the assessment of angiogenic changes in the microvascular architecture remains challenging. This article presents 2 models enabling the characterization of the microvascular architecture by DCE-MRI. THEORY: The microvascular architecture is reflected in the dispersion coefficient according to the convective dispersion equation. A solution of this equation, combined with the Tofts model, permits defining a dispersion model for magnetic resonance imaging. A reduced dispersion model is also presented. METHODS: The proposed models were evaluated for prostate cancer diagnosis. Dynamic contrast-enhanced magnetic resonance imaging was performed, and concentration-time curves were calculated in each voxel. The simultaneous generation of parametric maps related to permeability and dispersion was obtained through model fitting. A preliminary validation was carried out through comparison with the histology in 15 patients referred for radical prostatectomy. RESULTS: Cancer localization was accurate with both dispersion models, with an area under the receiver operating characteristic curve greater than 0.8. None of the compared parameters, aimed at assessing vascular permeability and perfusion, showed better results. CONCLUSIONS: A new DCE-MRI method is proposed to characterize the microvascular architecture through the assessment of intravascular dispersion, without the need for separate arterial-input-function estimation. The results are promising and encourage further research.

Evaluation of conventional, dynamic contrast enhanced and diffusion weighted MRI for quantitative Crohn's disease assessment with histopathology of surgical specimens.

OBJECTIVES: To prospectively compare conventional MRI sequences, dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging (DWI) with histopathology of surgical specimens in Crohn's disease. METHODS: 3-T MR enterography was performed in consecutive Crohn's disease patients scheduled for surgery within 4 weeks. One to four sections of interest per patient were chosen for analysis. Evaluated parameters included mural thickness, T1 ratio, T2 ratio; on DCE-MRI maximum enhancement (ME), initial slope of increase (ISI), time-to-peak (TTP); and on DWI apparent diffusion coefficient (ADC). These were compared with location-matched histopathological grading of inflammation (AIS) and fibrosis (FS) using Spearman correlation, Kruskal-Wallis and Chi-squared tests. RESULTS: Twenty patients (mean age 38 years, 12 female) were included and 50 sections (35 terminal ileum, 11 ascending colon, 2 transverse colon, 2 descending colon) were matched to AIS and FS. Mural thickness, T1 ratio, T2 ratio, ME and ISI correlated significantly with AIS, with moderate correlation (r = 0.634, 0.392, 0.485, 0.509, 0.525, respectively; all P < 0.05). Mural thickness, T1 ratio, T2 ratio, ME, ISI and ADC correlated significantly with FS (all P < 0.05). CONCLUSIONS: Quantitative parameters from conventional, DCE-MRI and DWI sequences correlate with histopathological scores of surgical specimens. DCE-MRI and DWI parameters provide additional information. KEY POINTS: • Conventional MR enterography can be used to assess Crohn's disease activity. • Several MRI parameters correlate with inflammation and fibrosis scores from histopathology. • Dynamic contrast enhanced imaging and diffusion weighted imaging give additional information. • Quantitative MRI parameters can be used as biomarkers to evaluate Crohn's disease activity.

Dynamic contrast-enhanced MRI in determining disease activity in perianal fistulizing Crohn disease: a pilot study.

OBJECTIVE: The objective of our study was to perform a semiquantitative analysis of dynamic contrast-enhanced MRI for the evaluation of disease activity and therapeutic response in patients with perianal fistulizing Crohn disease. SUBJECTS AND METHODS: Sixteen consecutively registered patients with perianal Crohn disease underwent pelvic MRI. A dynamic contrast-enhanced sequence was performed at 3 T (temporal resolution, 4.2 seconds) during i.v. contrast injection. Maximum enhancement, initial slope of increase, volume transfer constant (K(trans)), and the extravascular space fractional volume (x028B;(e)) were calculated in a region of interest drawn around the fistula. Perianal disease activity index, C-reactive protein concentration, and an MRI-based activity score were calculated as reference standards. Six patients underwent a second MRI examination 6 weeks after starting treatment with anti-tumor necrosis factor α (anti-TNF-α). RESULTS: Perianal disease activity index moderately correlated with maximum enhancement (r = 0.67, p = 0.005), initial slope of increase (r = 0.58, p = 0.018), and volume of enhancing pixels (r = 0.79, p < 0.001) but not with K(trans) or x028B;(e). Volume of enhancing pixels also correlated with C-reactive protein concentration and the MRI-based score (r = 0.52, p = 0.041; r = 0.79, p < 0.001). The K(trans) values had decreased significantly 6 weeks after the start of anti-TNF-α therapy. CONCLUSION: Maximum enhancement and initial slope of increase correlate with disease activity in perianal Crohn disease. K(trans) may be an indicator of the effect of therapy on patients starting anti-TNF-α treatment.

Characteristics of synovial inflammation in early arthritis analysed by pixel-by-pixel time-intensity curve shape analysis.

OBJECTIVE: Dynamic contrast-enhanced (DCE-MRI) time-intensity curve (TIC) shape analysis has previously been used in oncology, where fast initial enhancement and early washout are associated with malignancy. As RA synovium has some tumour-like features, we investigated DCE-MRI TIC shape expression in early arthritis in relationship to diagnosis. METHODS: Twenty-eight DMARD-naïve, early arthritis patients (<1 year) with inflammation of at least one knee joint were included. At baseline DCE-MRI of the inflamed knee joint was performed, and the TIC shape type expression, maximal enhancement, maximum slope of increase and total volume of enhancing pixels were calculated. In addition, disease activity parameters were determined. At 2 years of follow-up, patients were classified as RA or non-RA according to established classification criteria. RESULTS: Type 4 TIC shape, characterized by fast initial enhancement followed by a quick washout phase, was significantly higher in patients fulfilling classification criteria for RA after 2 years of follow-up compared with non-RA patients (15.6 and 7.9%, respectively, P = 0.02). All other DCE-MRI parameters showed no differences between the groups, highlighting the specificity of this observation. CONCLUSION: A high expression of aggressive DCE-MRI TIC shape Type 4 is associated with RA. Our results are consistent with the view that increased vascularity plays a key role in the pathogenesis of RA. This study underlines the rationale for further studies investigating the prospect of DCE-MRI TIC shape analysis as a diagnostic tool in early arthritis and the relationship with development of destructive disease.

Late effects of high-dose adjuvant chemotherapy on white and gray matter in breast cancer survivors: converging results from multimodal magnetic resonance imaging.

The neural substrate underlying cognitive impairments after chemotherapy is largely unknown. Here, we investigated very late (>9 years) effects of adjuvant high-dose chemotherapy on brain white and gray matter in primary breast cancer survivors (n = 17) with multimodal magnetic resonance imaging (MRI). A group of breast cancer survivors who did not receive chemotherapy was scanned for comparison (n = 15). Neuropsychological tests demonstrated cognitive impairments in the chemotherapy group. Diffusion tensor imaging (DTI) with tract-based spatial statistics showed that chemotherapy was associated with focal changes in DTI values indicative for reduced white matter integrity. Single voxel proton MR spectroscopy (1H-MRS) in the left centrum semiovale (white matter) showed a reduction of N-acetylasparate/creatine indicative of axonal injury. Voxel-based morphometry demonstrated a reduction of gray matter volume that overlapped with fMRI hypoactivation (as reported in a previous publication) in posterior parietal areas and colocalized with DTI abnormalities. Also, DTI correlated with 1H-MRS only in the chemotherapy group. These results converge to suggest that high-dose adjuvant chemotherapy for breast cancer is associated with long-term injury to white matter, presumably reflecting a combination of axonal degeneration and demyelination, and damage to gray matter with associated functional deficits. Hormonal treatment with tamoxifen may also have contributed to the observed effects, although results from other studies indicate that it is unlikely that tamoxifen is solely or largely responsible. Using this multimodality approach we provide for the first time insight into the neural substrate underlying cognitive impairments following systemic administration of cytotoxic agents many years after treatment.

Model-based, semiquantitative and time intensity curve shape analysis of dynamic contrast-enhanced MRI: a comparison in patients undergoing antiangiogenic treatment for recurrent glioma.

PURPOSE: To compare time intensity curve (TIC)-shape analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data with model-based analysis and semiquantitative analysis in patients with high-grade glioma treated with the antiangiogenic drug bevacizumab. MATERIALS AND METHODS: Fifteen patients had a pretreatment and at least one posttreatment DCE-MRI. We applied a pixel-by-pixel TIC shape analysis, where TICs are classified into five different types according to their shape, and calculated the occurrence of each TIC type in the region of interest (ROI). The results were compared to the pharmacokinetic model (PKM) parameters K(trans) , K(ep) , V(e) , and V(i) , and with the semiquantitative parameters maximum enhancement (ME) and initial slope of increase (ISI). RESULTS: The relative amount of type 2 and 4 TIC shape significantly correlated with the parameter K(ep) but not with K(trans) or V(e) . The PKM parameter V(e) and the semiquantitative parameters ME and ISI showed significant changes after treatment. None of the TIC shapes individually showed significant changes. CONCLUSION: The semiquantitative parameters ME and ISI are more sensitive to the effect of the bevacizumab than K(trans) and V(e) . The pixel-by-pixel TIC shape analysis parameters are not sensitive to the effect of bevacizumab, although they can be seen as surrogates for the PKM parameter K(ep) .

Reproducibility of the gadolinium concentration measurements and of the fitting parameters of the vascular input function in the superior sagittal sinus in a patient population.

It is widely recognised that the measurement of the arterial input function (AIF) is a key issue and a major source of errors in the pharmacokinetic modelling of dynamic, contrast-enhanced magnetic resonance imaging (DCE-MRI) data, and the modality of the AIF determination is still a matter of debate. In this study we addressed the problem of the intrinsic variability of the AIF within the imaged volume of a DCE-MRI scan by systematically investigating the change in the concentration of contrast agent over time and the fit parameters of the derived vascular input function (VIF) obtained from the superior sagittal sinus (SSS) of a patient population that was scanned longitudinally during treatment for high grade glioma. From a total of 82 scanning sessions, we compared the results obtained with three different DCE-MRI protocols and between two different fitting functions. We applied a correction algorithm to the measured concentration-time curves to minimize the effect of the low temporal resolution on the VIF, and investigated the effect of this algorithm on the reproducibility. Finally, where possible, we compared the signal obtained in the SSS to the signal obtained in the middle cerebral artery. We found a good intrapatient reproducibility of both the measured gadolinium concentrations and VIF parameters, and that the variation of the parameters due to slice location within a patient was significantly lower than the intra patient variation. Intrapatient, interscan differences were significantly less marked than inter-patient differences showing a good intraclass correlation coefficient. We did encounter a MRI protocol dependence of the VIF fitting parameters. The correction algorithm significantly improved the reproducibility of the fitting parameters. These results support the idea that the use of a patient specific measured AIF, not necessarily averaged over a large volume, offers a significant benefit with respect to an external AIF or a measured cohort average AIF.