AIM: To investigate whether subjective radiologist grading of motility on magnetic resonance enterography (MRE) is as effective as software quantification, and to determine the combination of motility metrics with the strongest association with symptom severity. MATERIALS AND METHODS: One hundred and five Crohn's disease patients (52 male, 53 female, 16–68 years old, mean age 34 years old) recruited from two sites underwent MRE, including a 20 second breath-hold cine motility sequence. Each subject completed a Harvey–Bradshaw Index (HBI) symptom questionnaire. Five features within normally appearing bowel were scored visually by two experienced radiologists, and then quantified using automated analysis software, including (1) mean motility, (2) spatial motility variation, (3) temporal motility variation, (4) area of motile bowel, (5) intestinal distension. Multivariable linear regression derived the combination of features with the highest association with HBI score. RESULTS: The best automated metric combination was temporal variation (p<0.05) plus area of motile bowel (p<0.05), achieving an R^{2 adjusted} value of 0.036. Spatial variation was also associated with symptoms (p<0.05, R^{2 adjusted} = 0.034); however, when visually assessed by radiologists, none of the features had a significant relationship with the HBI score. CONCLUSION: Software quantified temporal and spatial variability in bowel motility are associated with abdominal symptoms in Crohn's disease. Subjective radiologist assessment of bowel motility is insufficient to detect aberrant motility. Automated analysis of motility patterns holds promise as an objective biomarker for aberrant physiology underlying symptoms in enteric disorders.

Objectives: To compare Gd-EOB-DTPA dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) with ^99m Tc-mebrofenin hepatobiliary scintigraphy (HBS) as quantitative liver function tests for the preoperative assessment of patients undergoing liver resection. Methods: Patients undergoing liver surgery and preoperative assessment of future remnant liver (FRL) function using ^99m Tc-mebrofenin HBS were included. Patients underwent DHCE-MRI. Total liver uptake function was calculated for both modalities: mebrofenin uptake rate (MUR) and Ki respectively. The FRL was delineated with both SPECT-CT and MRI to calculate the functional share. Blood samples were taken to assess biochemical liver parameters. Results: A total of 20 patients were included. The HBS-derived MUR and the DHCE-MRI-derived mean Ki correlated strongly for both total and FRL function (Pearson r = 0.70, p = 0.001 and r = 0.89, p < 0.001 respectively). There was a strong agreement between the functional share determined with both modalities (ICC = 0.944, 95% CI 0.863–0.978, n = 20). There was a significant negative correlation between liver aminotransferases and bilirubin for both MUR and Ki. Conclusions: Assessment of liver function with DHCE-MRI is comparable with that of ^99m Tc-mebrofenin HBS and has the potential to be combined with diagnostic MRI imaging. This can therefore provide a one-stop-shop modality for the preoperative assessment of patients undergoing liver surgery. Key Points: • Quantitative assessment of liver function using hepatobiliary scintigraphy is performed in the preoperative assessment of patients undergoing liver surgery in order to prevent posthepatectomy liver failure. • Gd-EOB-DTPA dynamic hepatocyte-specific contrast-enhanced MRI (DHCE-MRI) is an emerging method to quantify liver function and can serve as a potential alternative to hepatobiliary scintigraphy. • Assessment of liver function with dynamic gadoxetate-enhanced MRI is comparable with that of hepatobiliary scintigraphy and has the potential to be combined with diagnostic MRI 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.

Rationale and Objectives: The objective of this study was to develop and validate a predictive magnetic resonance imaging (MRI) activity score for ileocolonic Crohn disease activity based on both subjective and semiautomatic MRI features. Materials and Methods: An MRI activity score (the “virtual gastrointestinal tract [VIGOR]” score) was developed from 27 validated magnetic resonance enterography datasets, including subjective radiologist observation of mural T2 signal and semiautomatic measurements of bowel wall thickness, excess volume, and dynamic contrast enhancement (initial slope of increase). A second subjective score was developed based on only radiologist observations. For validation, two observers applied both scores and three existing scores to a prospective dataset of 106 patients (59 women, median age 33) with known Crohn disease, using the endoscopic Crohn's Disease Endoscopic Index of Severity (CDEIS) as a reference standard. Results: The VIGOR score (17.1 × initial slope of increase + 0.2 × excess volume + 2.3 × mural T2) and other activity scores all had comparable correlation to the CDEIS scores (observer 1: r = 0.58 and 0.59, and observer 2: r = 0.34–0.40 and 0.43–0.51, respectively). The VIGOR score, however, improved interobserver agreement compared to the other activity scores (intraclass correlation coefficient = 0.81 vs 0.44–0.59). A diagnostic accuracy of 80%–81% was seen for the VIGOR score, similar to the other scores. Conclusions: The VIGOR score achieves comparable accuracy to conventional MRI activity scores, but with significantly improved reproducibility, favoring its use for disease monitoring and therapy evaluation.

The Couinaud classification of hepatic anatomy partitions the liver into eight functionally independent segments. Detection and segmentation of the hepatic vein (HV), portal vein (PV) and inferior vena cava (IVC) plays an important role in the subsequent delineation of the liver segments. To facilitate pharmacokinetic modeling of the liver based on the same data, a 4D DCE-MR scan protocol was selected. This yields images with high temporal resolution but low spatial resolution. Since the liver's vasculature consists of many tiny branches, segmentation of these images is challenging. The proposed framework starts with registration of the 4D DCE-MRI series followed by region growing from manually annotated seeds in the main branches of key blood vessels in the liver. It calculates the Pearson correlation between the time intensity curves (TICs) of a seed and all voxels. A maximum correlation map for each vessel is obtained by combining the correlation maps for all branches of the same vessel through a maximum selection per voxel. The maximum correlation map is incorporated in a level set scheme to individually delineate the main vessels. Subsequently, the eight liver segments are segmented based on three vertical intersecting planes fit through the three skeleton branches of HV and IVC's center of mass as well as a horizontal plane fit through the skeleton of PV. Our segmentation regarding delineation of the vessels is more accurate than the results of two state-of-the-art techniques on five subjects in terms of the average symmetric surface distance (ASSD) and modified Hausdorff distance (MHD). Furthermore, the proposed liver partitioning achieves large overlap with manual reference segmentations (expressed in Dice Coefficient) in all but a small minority of segments (mean values between 87% and 94% for segments 2-8). The lower mean overlap for segment 1 (72%) is due to the limited spatial resolution of our DCE-MR scan protocol.

Purpose: To develop a method for intra-patient registration of pre- and post-contrast abdominal MR images with large local deformations and large intensity variations. Method: A hybrid method is proposed to deal with this problem. It consists of two coupled techniques: (1) descriptor matching (DM) at the original resolution using a discrete optimization strategy to avoid getting trapped in a local minimum; (2) continuous optimization to refine the registration outcome based on autocorrelation of local image structure (ALOST). Our method—called DM-ALOST—has become insensitive to the local uptake of contrast agent by exploiting the mean phase and the phase congruency extracted from the multi-scale monogenic signal. The method was extensively tested on abdominal MR data of 30 patients with Crohn’s disease. Results: DM-ALOST produced significantly larger mean Dice coefficients than two state-of-the-art methods (Formula presented.). Conclusion: Both qualitative and quantitative tests demonstrated improved registration using the proposed method compared to the state-of-the-art. The DM-ALOST method facilitates measurement of corresponding features from different abdominal MR images, which can aid to assess certain diseases, particularly Crohn’s disease.

Purpose: The purpose of the study was to compare the performance of contrast-enhanced (CE)-MRI and diffusion-weighted imaging (DW)-MRI in grading Crohn’s disease activity of the terminal ileum. Methods: Three readers evaluated CE-MRI, DW-MRI, and their combinations (CE/DW-MRI and DW/CE-MRI, depending on which protocol was used at the start of evaluation). Disease severity grading scores were correlated to the Crohn’s Disease Endoscopic Index of Severity (CDEIS). Diagnostic accuracy, severity grading, and levels of confidence were compared between imaging protocols and interobserver agreement was calculated. Results: Sixty-one patients were included (30 female, median age 36). Diagnostic accuracy for active disease for CE-MRI, DW-MRI, CE/DW-MRI, and DW/CE-MRI ranged between 0.82 and 0.85, 0.75 and 0.83, 0.79 and 0.84, and 0.74 and 0.82, respectively. Severity grading correlation to CDEIS ranged between 0.70 and 0.74, 0.66 and 0.70, 0.69 and 0.75, and 0.67 and 0.74, respectively. For each reader, CE-MRI values were consistently higher than DW-MRI, albeit not significantly. Confidence levels for all readers were significantly higher for CE-MRI compared to DW-MRI (P < 0.001). Further increased confidence was seen when using combined imaging protocols. Conclusions: There was no significant difference of CE-MRI and DW-MRI in determining disease activity, but the higher confidence levels may favor CE-MRI. DW-MRI is a good alternative in cases with relative contraindications for the use of intravenous contrast medium.

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 v_p and K^trans) obtained with the three AIFs were compared. In the Crohn's patients K^trans 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 K^trans to CDEIS. Results: The median v_p 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 v_p were significantly larger with the ROI approach (P < 0.05 for all comparisons). In the Crohn's disease study, the estimated K^trans 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 K^trans parameter with CDEIS, compared to existing approaches. Level of Evidence: 3. Technical Efficacy Stage 1. J. Magn. Reson. Imaging 2018;47:1197–1204.

Objective: To evaluate a semi-automatic method for delineation of the bowel wall and measurement of the wall thickness in patients with Crohn's disease. Methods: 53 patients with suspected or proven Crohn's disease were selected. Two radiologists independently supervised the delineation of regions with active Crohn's disease on MRI, yielding manual annotations (Ano1, Ano2). Three observers manually measured the maximal bowel wall thickness of each annotated segment. An active contour segmentation approach semi-automatically delineated the bowel wall. For each active region, two segmentations (Seg1, Seg2) were obtained by independent observers, in which the maximum wall thickness was automatically determined. The overlap between (Seg1, Seg2) was compared with the overlap of (Ano1, Ano2) using Wilcoxon's signed rank test. The corresponding variances were compared using the Brown-Forsythe test. The variance of the semi-automatic thickness measurements was compared with the overall variance of manual measurements through an F-test. Furthermore, the intraclass correlation coefficient (ICC) of semiautomatic thickness measurements was compared with the ICC of manual measurements through a likelihood-ratio test. Results: Patient demographics: median age, 30 years; interquartile range, 25-38 years; 33 females. The median overlap of the semi-automatic segmentations (Seg1 vs Seg2: 0.89) was significantly larger than the median overlap of the manual annotations (Ano1 vs Ano2: 0.72); p=1.4×1025. The variance in overlap of the semiautomatic segmentations was significantly smaller than the variance in overlap of the manual annotations (p=1.1×1029). The variance of the semi-automated measurements (0.46mm2) was significantly smaller than the variance of the manual measurements (2.90mm2, p=1.1×1027). The ICC of semi-automatic measurement (0.88) was significantly higher than the ICC of manual measurement (0.45); p=0.005. Conclusion: The semi-automatic technique facilitates reproducible delineation of regions with active Crohn's disease. The semi-automatic thickness measurement sustains significantly improved interobserver agreement. Advances in knowledge: Automation of bowel wall thickness measurements strongly increases reproducibility of these measurements, which are commonly used in MRI scoring systems of Crohn's disease activity.

In Dynamic Contrast-Enhanced MRI (DCE-MRI) of the liver, a series of images is acquired over a period of 20 minutes. Due to the patient's breathing, the liver is subject to a substantial displacement between acquisitions. Furthermore, due to its location in the abdomen, the liver also undergoes marked deformation. The large deformations combined with variation in image contrast make accurate liver registration challenging. We present a registration framework that incorporates a liver segmentation to improve the registration accuracy. The segmented liver serves as region-of-interest to our in-house developed registration method called ALOST (autocorrelation of local image structure). ALOST is a continuous optimization method that uses local phase features to overcome space-variant intensity distortions. The proposed framework can confine the solution field to the liver and allow for ALOST to obtain a more accurate solution. For the segmentation part, we use a level-set method to delineate the liver in a so-called contrast enhancement map. This map is obtained by computing the difference between the last and registered first volume from the DCE series. Subsequently, we slightly dilate the segmentation, and apply it as the mask to the other DCE-MRI volumes during registration. It is shown that the registration result becomes more accurate compared with the original ALOST approach.