Reliability of MR Enterography Features for Describing Fibrostenosing Crohn Disease.

Background Clinical decision making and drug development for fibrostenosing Crohn disease is constrained by a lack of imaging definitions, scoring conventions, and validated end points. Purpose To assess the reliability of MR enterography features to describe Crohn disease strictures and determine correlation with stricture severity. Materials and Methods A retrospective study of patients with symptomatic terminal ileal Crohn disease strictures who underwent MR enterography at tertiary care centers (Cleveland Clinic: September 2013 to November 2020; Mayo Clinic: February 2008 to March 2019) was conducted by using convenience sampling. In the development phase, blinded and trained radiologists independently evaluated 26 MR enterography features from baseline and follow-up examinations performed more than 6 months apart, with no bowel resection performed between examinations. Follow-up examinations closest to 12 months after baseline were selected. Reliability was assessed using the intraclass correlation coefficient (ICC). In the validation phase, after five features were redefined, reliability was re-estimated in an independent convenience sample using baseline examinations. Multivariable linear regression analysis identified features with at least moderate interrater reliability (ICC ≥0.41) that were independently associated with stricture severity. Results Ninety-nine (mean age, 40 years ± 14 [SD]; 50 male) patients were included in the development group and 51 (mean age, 45 years ± 16 [SD]; 35 female) patients were included in the validation group. In the development group, nine features had at least moderate interrater reliability. One additional feature demonstrated moderate reliability in the validation group. Stricture length (ICC = 0.85 [95% CI: 0.75, 0.91] and 0.91 [95% CI: 0.75, 0.96] in development and validation phase, respectively) and maximal associated small bowel dilation (ICC = 0.74 [95% CI: 0.63, 0.80] and 0.73 [95% CI: 0.58, 0.87] in development and validation group, respectively) had the highest interrater reliability. Stricture length, maximal stricture wall thickness, and maximal associated small bowel dilation were independently (regression coefficients, 0.09-3.97; P < .001) associated with stricture severity. Conclusion MR enterography definitions and scoring conventions for reliably assessing features of Crohn disease strictures were developed and validated, and feature correlation with stricture severity was determined. © RSNA, 2024 Supplemental material is available for this article. See also the article by Rieder and Ma et al in this issue. See also the editorial by Galgano and Summerlin in this issue.

Optimizing pseudo-spiral sampling for abdominal DCE MRI using a digital anthropomorphic phantom.

PURPOSE: For reliable DCE MRI parameter estimation, k-space undersampling is essential to meet resolution, coverage, and signal-to-noise requirements. Pseudo-spiral (PS) sampling achieves this by sampling k-space on a Cartesian grid following a spiral trajectory. The goal was to optimize PS k-space sampling patterns for abdomin al DCE MRI. METHODS: The optimal PS k-space sampling pattern was determined using an anthropomorphic digital phantom. Contrast agent inflow was simulated in the liver, spleen, pancreas, and pancreatic ductal adenocarcinoma (PDAC). A total of 704 variable sampling and reconstruction approaches were created using three algorithms using different parametrizations to control sampling density, halfscan and compressed sensing regularization. The sampling patterns were evaluated based on image quality scores and the accuracy and precision of the DCE pharmacokinetic parameters. The best and worst strategies were assessed in vivo in five healthy volunteers without contrast agent administration. The best strategy was tested in a DCE scan of a PDAC patient. RESULTS: The best PS reconstruction was found to be PS-diffuse based, with quadratic distribution of readouts on a spiral, without random shuffling, halfscan factor of 0.8, and total variation regularization of 0.05 in the spatial and temporal domains. The best scoring strategy showed sharper images with less prominent artifacts in healthy volunteers compared to the worst strategy. Our suggested DCE sampling strategy also showed high quality DCE images in the PDAC patient. CONCLUSION: Using an anthropomorphic digital phantom, we identified an optimal PS sampling strategy for abdominal DCE MRI, and demonstrated feasibility in a PDAC patient.

Prognostic value of total tumor volume in patients with colorectal liver metastases: A secondary analysis of the randomized CAIRO5 trial with external cohort validation.

BACKGROUND: This study aimed to assess the prognostic value of total tumor volume (TTV) for early recurrence (within 6 months) and overall survival (OS) in patients with colorectal liver metastases (CRLM), treated with induction systemic therapy followed by complete local treatment. METHODS: Patients with initially unresectable CRLM from the multicenter randomized phase 3 CAIRO5 trial (NCT02162563) who received induction systemic therapy followed by local treatment were included. Baseline TTV and change in TTV as response to systemic therapy were calculated using the CT scan before and the first after systemic treatment, and were assessed for their added prognostic value. The findings were validated in an external cohort of patients treated at a tertiary center. RESULTS: In total, 215 CAIRO5 patients were included. Baseline TTV and absolute change in TTV were significantly associated with early recurrence (P = 0.005 and P = 0.040, respectively) and OS in multivariable analyses (P = 0.024 and P = 0.006, respectively), whereas RECIST1.1 was not prognostic for early recurrence (P = 0.88) and OS (P = 0.35). In the validation cohort (n = 85), baseline TTV and absolute change in TTV remained prognostic for early recurrence (P = 0.041 and P = 0.021, respectively) and OS in multivariable analyses (P < 0.0001 and P = 0.012, respectively), and showed added prognostic value over conventional clinicopathological variables (increase C-statistic, 0.06; 95 % CI, 0.02 to 0.14; P = 0.008). CONCLUSION: Total tumor volume is strongly prognostic for early recurrence and OS in patients who underwent complete local treatment of initially unresectable CRLM, both in the CAIRO5 trial and the validation cohort. In contrast, RECIST1.1 did not show prognostic value for neither early recurrence nor OS.

Added Value of Liver MRI in Patients Eligible for Surgical Resection or Ablation of Colorectal Liver Metastases Based on CT: A Systematic Review and Meta-Analysis.

Background: Abdominal computed tomography (CT) is the standard imaging modality for detection and staging in patients with colorectal liver metastases (CRLM). Although liver magnetic resonance imaging (MRI) is superior to CT in detecting small lesions, guidelines are ambiguous regarding the added value of an additional liver MRI in the surgical workup of patients with CRLM. Therefore, this systematic review and meta-analysis aimed to evaluate the clinical added value of liver MRI in patients eligible for resection or ablation of CRLM based on CT. Methods: A systematic search was performed in the PubMed, Embase, and Cochrane Library databases through June 23, 2023. Studies investigating the impact of additional MRI on local treatment plan following CT in patients with CRLM were included. Risk of bias was assessed using the QUADAS-2 tool. The pooled weighted proportions for the primary outcome were calculated using random effect meta-analysis. Results: Overall, 11 studies with 1440 patients were included, of whom 468 patients (32.5%) were assessed for change in local treatment plan. Contrast-enhanced liver MRI was used in 10 studies, including gadoxetic acid in 9 studies. Liver MRI with diffusion-weighted imaging was used in 8 studies. Pooling of data found a 24.12% (95% confidence interval, 15.58%-32.65%) change in the local treatment plan based on the added findings of liver MRI following CT. Sensitivity analysis including 5 studies (268 patients) focusing on monophasic portal venous CT followed by gadoxetic acid-enhanced liver MRI with diffusion-weighted imaging showed a change of local treatment plan of 17.88% (95% confidence interval, 5.14%-30.62%). Conclusions: This systematic review and meta-analysis found that liver MRI changed the preinterventional local treatment plan in approximately one-fifth of patients eligible for surgical resection or ablation of CRLM based on CT. These findings suggest a clinically relevant added value of routine liver MRI in the preinterventional workup of CRLM, which should be confirmed by large prospective studies.

Free-breathing motion corrected magnetic resonance elastography of the abdomen.

Background: Magnetic resonance elastography (MRE) is a non-invasive method to measure the viscoelastic properties of tissue and has been applied in multiple abdominal organs. However, abdominal MRE suffers from detrimental breathing motion causing misalignment of structures between repeated acquisitions for different MRE dimensions (e.g., motion encoding directions and wave phase offsets). This study investigated motion correction strategies to resolve all breathing motion on sagittal free-breathing MRE acquisitions in a phantom, in healthy volunteers and showed feasibility in patients. Methods: First, in silico experiments were performed on a static phantom dataset with simulated motion. Second, eight healthy volunteers underwent two sagittal MRE acquisitions in the pancreas and right kidney. The multi-frequency free-breathing spin-echo echo-planar-imaging (SE-EPI) MRE consisted of four frequencies (30, 40, 50, 60 Hz), eight wave-phase offsets, with 3 mm3 isotropic voxel size. Following data re-sorting in different number of motion states (4 till 12) based on respiratory waveform signal, three intensity-based registration methods (monomodal, multimodal, and phase correlation) and non-rigid local registration were compared. A ranking method was used to determine the best registration method, based on seven signal-to-noise and image quality measures. Repeatability was assessed for no motion correction (Original) and the best performing method (Best) using Bland-Altman analysis. Lastly, the best motion correction method was compared to no motion correction on patient MRE data [pancreatic ductal adenocarcinoma (PDAC, n=5) and metabolic dysfunction-associated steatotic liver disease (MASLD) (n=1)]. Results: In silico experiments showed a deviation of shear wave speed (SWS) with simulated motion to the ground truth, which was (partially) resolved using motion correction. In healthy volunteers ranking resulted in the best motion correction method of monomodal registration using nine motion states, while no motion correction was ranked last. Limits of agreement were (-0.18, 0.14), and (-0.25, 0.18) m/s for Best and Original, respectively. Using motion correction in patients resulted in a significant increase in SWS in the pancreas (Original: 1.39±0.10 and Best: 1.50±0.17 m/s). After motion correction PDAC had a mean SWS of 1.56±0.27 m/s (Original: 1.42±0.25 m/s). The fibrotic liver mean SWS was 2.07±0.20 m/s (Original: 2.12±0.18 m/s). Conclusions: Motion correction in sagittal free-breathing abdominal MRE results in improved data quality, inversion precision, repeatability, and is feasible in patients.

Development and Validation of the Scoring System of Appendicitis Severity 2.0.

Importance: When considering nonoperative treatment in a patient with acute appendicitis, it is crucial to accurately rule out complicated appendicitis. The Atema score, also referred to as the Scoring System of Appendicitis Severity (SAS), has been designed to differentiate between uncomplicated and complicated appendicitis but has not been prospectively externally validated. Objective: To externally validate the SAS and, in case of failure, to develop an improved SAS (2.0) for estimating the probability of complicated appendicitis. Design, Setting, and Participants: This prospective study included adult patients who underwent operations for suspected acute appendicitis at 11 hospitals in the Netherlands between January 2020 and August 2021. Main Outcomes and Measures: Appendicitis severity was predicted according to the SAS in 795 patients and its sensitivity and negative predictive value (NPV) for complicated appendicitis were calculated. Since the predefined targets of 95% for both were not met, the SAS 2.0 was developed using the same cohort. This clinical prediction model was developed with multivariable regression using clinical, biochemical, and imaging findings. The SAS 2.0 was externally validated in a temporal validation cohort consisting of 565 patients. Results: In total, 1360 patients were included, 463 of whom (34.5%) had complicated appendicitis. Validation of the SAS resulted in a sensitivity of 83.6% (95% CI, 78.8-87.6) and an NPV of 85.0% (95% CI, 80.6-88.8), meaning that the predefined targets were not achieved. Therefore, the SAS 2.0 was developed, internally validated (C statistic, 0.87; 95% CI, 0.84-0.89), and subsequently externally validated (C statistic, 0.86; 95% CI, 0.82-0.89). The SAS 2.0 was designed to calculate a patient's individual probability of having complicated appendicitis along with a 95% CI. Conclusions and Relevance: In this study, external validation of the SAS fell short in accurately distinguishing complicated from uncomplicated appendicitis. The newly developed and externally validated SAS 2.0 was able to assess an individual patient's probability of having complicated appendicitis with high accuracy in patients with acute appendicitis. Use of this patient-specific risk assessment tool can be helpful when considering and discussing nonoperative treatment of acute appendicitis with patients.

Artificial intelligence for assessment of vascular involvement and tumor resectability on CT in patients with pancreatic cancer.

OBJECTIVE: This study aimed to develop and evaluate an automatic model using artificial intelligence (AI) for quantifying vascular involvement and classifying tumor resectability stage in patients with pancreatic ductal adenocarcinoma (PDAC), primarily to support radiologists in referral centers. Resectability of PDAC is determined by the degree of vascular involvement on computed tomography scans (CTs), which is associated with considerable inter-observer variability. METHODS: We developed a semisupervised machine learning segmentation model to segment the PDAC and surrounding vasculature using 613 CTs of 467 patients with pancreatic tumors and 50 control patients. After segmenting the relevant structures, our model quantifies vascular involvement by measuring the degree of the vessel wall that is in contact with the tumor using AI-segmented CTs. Based on these measurements, the model classifies the resectability stage using the Dutch Pancreatic Cancer Group criteria as either resectable, borderline resectable, or locally advanced (LA). RESULTS: We evaluated the performance of the model using a test set containing 60 CTs from 60 patients, consisting of 20 resectable, 20 borderline resectable, and 20 locally advanced cases, by comparing the automated analysis obtained from the model to expert visual vascular involvement assessments. The model concurred with the radiologists on 227/300 (76%) vessels for determining vascular involvement. The model's resectability classification agreed with the radiologists on 17/20 (85%) resectable, 16/20 (80%) for borderline resectable, and 15/20 (75%) for locally advanced cases. CONCLUSIONS: This study demonstrates that an AI model may allow automatic quantification of vascular involvement and classification of resectability for PDAC. RELEVANCE STATEMENT: This AI model enables automated vascular involvement quantification and resectability classification for pancreatic cancer, aiding radiologists in treatment decisions, and potentially improving patient outcomes. KEY POINTS: • High inter-observer variability exists in determining vascular involvement and resectability for PDAC. • Artificial intelligence accurately quantifies vascular involvement and classifies resectability for PDAC. • Artificial intelligence can aid radiologists by automating vascular involvement and resectability assessments.

Marked difference in liver fat measured by histology vs. magnetic resonance-proton density fat fraction: A meta-analysis.

Background & Aims: Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease. Methods: Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies. Results: Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology. Conclusions: Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values. Impact and implications: Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.