Quantification of Multi-Compartment Flow with Spectral Diffusion MRI.

Purpose: Estimation of multi-compartment intravoxel 'flow' in fD in ml/100g/min with multi-b-value diffusion weighted imaging and a multi-Gaussian model in the kidneys. Theory and Methods: A multi-Gaussian model of intravoxel flow using water transport time to quantify f D (ml/100g/min) is presented and simulated. Multi-compartment anisotropic DWI signal is simulated with Rician noise and SNR=50 and analyzed with a rigid bi-exponential, a rigid tri-exponential and diffusion spectrum imaging model of intravoxel incoherent motion (spectral diffusion) to study extraction of multi-compartment flow. The regularization parameter for spectral diffusion is varied to study the impact on the resulting spectrum and computation speed. The application is demonstrated in a two-center study of 54 kidney allografts with 9 b-value advanced DWI that were split by function (CKD-EPI 2021 eGFR<45ml/min/1.73m2) and fibrosis (Banff 2017 interstitial fibrosis and tubular atrophy score 0-6) to demonstrate multi-compartment flow of various kidney pathologies. Results: Simulation of anisotropic multi-compartment flow from spectral diffusion demonstrated strong correlation to truth for both three-compartment anisotropic diffusion ( y = 1.08 x + 0.1 , R 2 = 0.71 ) and two-compartment anisotropic diffusion ( y = 0.91 + 0.6 , R 2 = 0.74 ), outperforming rigid models in cases of variable compartment number. Use of a fixed regularization parameter set to λ = 0.1 increased computation up to 208-fold and agreed with voxel-wise cross-validated regularization (concordance correlation coefficient=0.99). Spectral diffusion of renal allografts showed decreasing trend of tubular and vascular flow with higher levels of fibrosis, and significant increase in tissue parenchyma flow (f-stat=3.86, p=0.02). Tubular f D was significantly decreased in allografts with impaired function (eGFR<45ml/min/1.73m2)(Mann-Whitney U t-stat=-2.14, p=0.04). Conclusions: Quantitative multi-compartment intravoxel 'flow' can be estimated in ml/100g/min with f D from multi-Gaussian diffusion with water transport time, even with moderate anisotropy such as in kidneys. The use of spectral diffusion with a multi-Gaussian model and a fixed regularization parameter is particularly promising in organs such as the kidney with variable numbers of physiologic compartments.

The Spatial Extracellular Proteomic Tumor Microenvironment Distinguishes Molecular Subtypes of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) mortality rates continue to increase faster than those of other cancer types due to high heterogeneity, which limits diagnosis and treatment. Pathological and molecular subtyping have identified that HCC tumors with poor outcomes are characterized by intratumoral collagenous accumulation. However, the translational and post-translational regulation of tumor collagen, which is critical to the outcome, remains largely unknown. Here, we investigate the spatial extracellular proteome to understand the differences associated with HCC tumors defined by Hoshida transcriptomic subtypes of poor outcome (Subtype 1; S1; n = 12) and better outcome (Subtype 3; S3; n = 24) that show differential stroma-regulated pathways. Collagen-targeted mass spectrometry imaging (MSI) with the same-tissue reference libraries, built from untargeted and targeted LC-MS/MS was used to spatially define the extracellular microenvironment from clinically-characterized, formalin-fixed, paraffin-embedded tissue sections. Collagen α-1(I) chain domains for discoidin-domain receptor and integrin binding showed distinctive spatial distribution within the tumor microenvironment. Hydroxylated proline (HYP)-containing peptides from the triple helical regions of fibrillar collagens distinguished S1 from S3 tumors. Exploratory machine learning on multiple peptides extracted from the tumor regions could distinguish S1 and S3 tumors (with an area under the receiver operating curve of ≥0.98; 95% confidence intervals between 0.976 and 1.00; and accuracies above 94%). An overall finding was that the extracellular microenvironment has a high potential to predict clinically relevant outcomes in HCC.

Lemann Index for assessing bowel damage in Crohn's disease: a real world study.

BACKGROUND & AIMS: The Lemann Index (LI), an endpoint to measure cumulative structural bowel damage in Crohn's disease (CD), has been recently updated and validated. We applied this to investigate predictors of bowel damage in a real-world cohort. METHODS: We performed a retrospective study (2008-2022) involving two tertiary referral IBD centers in the US. MR or CT enterographies were reviewed by study radiologists and endoscopy reports by study gastroenterologists, to calculate LI. Baseline and follow-up LI were calculated. We defined high bowel damage as LI ≥2. Factors associated with high LI were identified in patients with ≥2 LI scores using multivariate logistic regression and then assessed for a change in LI (increase vs. no change/decrease) using a multivariate linear mixed-effects model. RESULTS: 447 patients with CD had a median first LI of 7 [IQR, 1.25-14.55]. Median LI scores were significantly different when categorized by disease duration; 2.0 [IQR, 0.6-5.9] for <2 years, 2.6 [IQR, 0.6-9.6] for ≥2 and <10 years, and 12.5 [IQR, 6.4-21.5] for ≥10 years with a p <0.01. Disease duration, presence of perianal disease, elevated C-reactive protein, and Harvey-Bradshaw index, were associated with a high LI at inclusion and increase in LI during follow-up (all p <0.01). CONCLUSIONS: The updated LI quantified cross-sectional and longitudinal cumulative bowel damage in a real-world cohort of patients with CD with predictors identified for a longitudinal increase in LI. Further studies for prospective validation of LI and identification of multi-omic predictors of bowel damage are needed.

Imaging cholangiocarcinoma: CT and MRI techniques.

Cross-sectional imaging plays a crucial role in the detection, diagnosis, staging, and resectability assessment of intra- and extrahepatic cholangiocarcinoma. Despite this vital function, there is a lack of standardized CT and MRI protocol recommendations for imaging cholangiocarcinoma, with substantial differences in image acquisition across institutions and vendor platforms. In this review, we present standardized strategies for the optimal imaging assessment of cholangiocarcinoma including contrast media considerations, patient preparation recommendations, optimal contrast timing, and representative CT and MRI protocols with individual sequence optimization recommendations. Our recommendations are supported by expert opinion from members of the Society of Abdominal Radiology's Disease-Focused Panel (DFP) on Cholangiocarcinoma, encompassing a broad array of institutions and practice patterns.

Precision and Test-Retest Repeatability of Stiffness Measurement with MR Elastography: A Multicenter Phantom Study.

Background MR elastography (MRE) has been shown to have excellent performance for noninvasive liver fibrosis staging. However, there is limited knowledge regarding the precision and test-retest repeatability of stiffness measurement with MRE in the multicenter setting. Purpose To determine the precision and test-retest repeatability of stiffness measurement with MRE across multiple centers using the same phantoms. Materials and Methods In this study, three cylindrical phantoms made of polyvinyl chloride gel mimicking different degrees of liver stiffness in humans (phantoms 1-3: soft, medium, and hard stiffness, respectively) were evaluated. Between January 2021 and January 2022, phantoms were circulated between five different centers and scanned with 10 MRE-equipped clinical 1.5-T and 3-T systems from three major vendors, using two-dimensional (2D) gradient-recalled echo (GRE) imaging and/or 2D spin-echo (SE) echo-planar imaging (EPI). Similar MRE acquisition parameters, hardware, and reconstruction algorithms were used at each center. Mean stiffness was measured by a single observer for each phantom and acquisition on a single section. Stiffness measurement precision and same-session test-retest repeatability were assessed using the coefficient of variation (CV) and the repeatability coefficient (RC), respectively. Results The mean precision represented by the CV was 5.8% (95% CI: 3.8, 7.7) for all phantoms and both sequences combined. For all phantoms, 2D GRE achieved a CV of 4.5% (95% CI: 3.3, 5.7) whereas 2D SE EPI achieved a CV of 7.8% (95% CI: 3.1, 12.6). The mean RC of stiffness measurement was 5.8% (95% CI: 3.7, 7.8) for all phantoms and both sequences combined, 4.9% (95% CI: 2.7, 7.0) for 2D GRE, and 7.0% (95% CI: 2.9, 11.2) for 2D SE EPI (all phantoms). Conclusion MRE had excellent in vitro precision and same-session test-retest repeatability in the multicenter setting when similar imaging protocols, hardware, and reconstruction algorithms were used. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Tang in this issue.

Artificial intelligence in liver cancer research: a scientometrics analysis of trends and topics.

Background and aims: With the rapid growth of artificial intelligence (AI) applications in various fields, understanding its impact on liver cancer research is paramount. This scientometrics project aims to investigate publication trends and topics in AI-related publications in liver cancer. Materials and Methods: We employed a search strategy to identify AI-related publications in liver cancer using Scopus database. We analyzed the number of publications, author affiliations, and journals that publish AI-related publications in liver cancer. Finally, the publications were grouped based on intended application. Results: We identified 3950 eligible publications (2695 articles, 366 reviews, and 889 other document types) from 1968 to August 3, 2023. There was a 12.7-fold increase in AI-related publications from 2013 to 2022. By comparison, the number of total publications on liver cancer increased by 1.7-fold. Our analysis revealed a significant shift in trends of AI-related publications on liver cancer in 2019. We also found a statistically significant consistent increase in numbers of AI-related publications over time (tau = 0.756, p < 0.0001). Eight (53%) of the top 15 journals with the most publications were radiology journals. The largest number of publications were from China (n=1156), the US (n=719), and Germany (n=236). The three most common publication categories were "medical image analysis for diagnosis" (37%), "diagnostic or prognostic biomarkers modeling & bioinformatics" (19%), and "genomic or molecular analysis" (18%). Conclusion: Our study reveals increasing interest in AI for liver cancer research, evidenced by a 12.7-fold growth in related publications over the past decade. A common application of AI is in medical imaging analysis for various purposes. China, the US, and Germany are leading contributors.

Characterization of renal masses with MRI-based radiomics: assessment of inter-package and inter-observer reproducibility in a prospective pilot study.

OBJECTIVES: To evaluate radiomics features' reproducibility using inter-package/inter-observer measurement analysis in renal masses (RMs) based on MRI and to employ machine learning (ML) models for RM characterization. METHODS: 32 Patients (23M/9F; age 61.8 ± 10.6 years) with RMs (25 renal cell carcinomas (RCC)/7 benign masses; mean size, 3.43 ± 1.73 cm) undergoing resection were prospectively recruited. All patients underwent 1.5 T MRI with T2-weighted (T2-WI), diffusion-weighted (DWI)/apparent diffusion coefficient (ADC), and pre-/post-contrast-enhanced T1-weighted imaging (T1-WI). RMs were manually segmented using volume of interest (VOI) on T2-WI, DWI/ADC, and T1-WI pre-/post-contrast imaging (1-min, 3-min post-injection) by two independent observers using two radiomics software packages for inter-package and inter-observer assessments of shape/histogram/texture features common to both packages (104 features; n = 26 patients). Intra-class correlation coefficients (ICCs) were calculated to assess inter-observer and inter-package reproducibility of radiomics measurements [good (ICC ≥ 0.8)/moderate (ICC = 0.5-0.8)/poor (ICC < 0.5)]. ML models were employed using reproducible features (between observers and packages, ICC > 0.8) to distinguish RCC from benign RM. RESULTS: Inter-package comparisons demonstrated that radiomics features from T1-WI-post-contrast had the highest proportion of good/moderate ICCs (54.8-58.6% for T1-WI-1 min), while most features extracted from T2-WI, T1-WI-pre-contrast, and ADC exhibited poor ICCs. Inter-observer comparisons found that radiomics measurements from T1-WI pre/post-contrast and T2-WI had the greatest proportion of features with good/moderate ICCs (95.3-99.1% T1-WI-post-contrast 1-min), while ADC measurements yielded mostly poor ICCs. ML models generated an AUC of 0.71 [95% confidence interval = 0.67-0.75] for diagnosis of RCC vs. benign RM. CONCLUSION: Radiomics features extracted from T1-WI-post-contrast demonstrated greater inter-package and inter-observer reproducibility compared to ADC, with fair accuracy for distinguishing RCC from benign RM. CLINICAL RELEVANCE: Knowledge of reproducibility of MRI radiomics features obtained on renal masses will aid in future study design and may enhance the diagnostic utility of radiomics models for renal mass characterization.

Imaging-based noninvasive liver disease assessment for staging liver fibrosis in chronic liver disease: A systematic review supporting the AASLD Practice Guideline.

BACKGROUND AND AIMS: Transient elastography (TE), shear wave elastography, and/or magnetic resonance elastography (MRE), each providing liver stiffness measurement (LSM), are the most studied imaging-based noninvasive liver disease assessment (NILDA) techniques. To support the American Association for the Study of Liver Diseases guidelines on NILDA, we summarized the evidence on the accuracy of these LSM methods to stage liver fibrosis (F). APPROACH AND RESULTS: A comprehensive search for studies assessing LSM by TE, shear wave elastography, or MRE for the identification of significant fibrosis (F2-4), advanced fibrosis (F3-4), or cirrhosis (F4), using histopathology as the standard of reference by liver disease etiology in adults or children from inception to April 2022 was performed. We excluded studies with <50 patients with a single disease entity and mixed liver disease etiologies (with the exception of HCV/HIV coinfection). Out of 9447 studies, 240 with 61,193 patients were included in this systematic review. In adults, sensitivities for the identification of F2-4 ranged from 51% to 95%, for F3-4 from 70% to 100%, and for F4 from 60% to 100% across all techniques/diseases, whereas specificities ranged from 36% to 100%, 74% to 100%, and 67% to 99%, respectively. The largest body of evidence available was for TE; MRE appeared to be the most accurate method. Imaging-based NILDA outperformed blood-based NILDA in most comparisons, particularly for the identification of F3-4/F4. In the pediatric population, imaging-based NILDA is likely as accurate as in adults. CONCLUSIONS: LSM from TE, shear wave elastography, and MRE shows acceptable to outstanding accuracy for the detection of liver fibrosis across various liver disease etiologies. Accuracy increased from F2-4 to F3-4 and was the highest for F4. Further research is needed to better standardize the use of imaging-based NILDA, particularly in pediatric liver diseases.

MRI Gadolinium-Based Contrast Media: Meeting Radiological, Clinical, and Environmental Needs.

Gadolinium-based contrast agents (GBCAs) are routinely used in magnetic resonance imaging (MRI). They are essential for choosing the most appropriate medical or surgical strategy for patients with serious pathologies, particularly in oncologic, inflammatory, and cardiovascular diseases. However, GBCAs have been associated with an increased risk of nephrogenic systemic fibrosis in patients with renal failure, as well as the possibility of deposition in the brain, bones, and other organs, even in patients with normal renal function. Research is underway to reduce the quantity of gadolinium injected, without compromising image quality and diagnosis. The next generation of GBCAs will enable a reduction in the gadolinium dose administered. Gadopiclenol is the first of this new generation of GBCAs, with high relaxivity, thus having the potential to reduce the gadolinium dose while maintaining good in vivo stability due to its macrocyclic structure. High-stability and high-relaxivity GBCAs will be one of the solutions for reducing the dose of gadolinium to be administered in clinical practice, while the development of new technologies, including optimization of MRI acquisitions, new contrast mechanisms, and artificial intelligence may help reduce the need for GBCAs. Future solutions may involve a combination of next-generation GBCAs and image-processing techniques to optimize diagnosis and treatment planning while minimizing exposure to gadolinium. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Early post-treatment MRI predicts long-term hepatocellular carcinoma response to radiation segmentectomy.

OBJECTIVES: Radiation segmentectomy using yttrium-90 plays an emerging role in the management of early-stage HCC. However, the value of early post-treatment MRI for response assessment is uncertain. We assessed the value of response criteria obtained early after radiation segmentectomy in predicting long-term response in patients with HCC. MATERIALS AND METHODS: Patients with HCC who underwent contrast-enhanced MRI before, early, and 12 months after radiation segmentectomy were included in this retrospective single-center study. Three independent radiologists reviewed images at baseline and 1st follow-up after radiation segmentectomy and assessed lesion-based response according to mRECIST, LI-RADS treatment response algorithm (TRA), and image subtraction. The endpoint was response at 12 months based on consensus readout of two separate radiologists. Diagnostic accuracy for predicting complete response (CR) at 12 months based on the 1st post-treatment MRI was calculated. RESULTS: Eighty patients (M/F 60/20, mean age 67.7 years) with 80 HCCs were assessed (median size baseline, 1.8 cm [IQR, 1.4-2.9 cm]). At 12 months, 74 patients were classified as CR (92.5%), 5 as partial response (6.3%), and 1 as progressive disease (1.2%). Diagnostic accuracy for predicting CR was fair to good for all readers with excellent positive predictive value (PPV): mRECIST (range between 3 readers, accuracy: 0.763-0.825, PPV: 0.966-1), LI-RADS TRA (accuracy: 0.700-0.825, PPV: 0.983-1), and subtraction (accuracy: 0.775-0.825, PPV: 0.967-1), with no difference in accuracy between criteria (p range 0.053 to > 0.9). CONCLUSION: mRECIST, LI-RADS TRA, and subtraction obtained on early post-treatment MRI show similar performance for predicting long-term response in patients with HCC treated with radiation segmentectomy. CLINICAL RELEVANCE STATEMENT: Response assessment extracted from early post-treatment MRI after radiation segmentectomy predicts complete response in patients with HCC with high PPV (≥ 0.96). KEY POINTS: • Early post-treatment response assessment on MRI predicts response in patients with HCC treated with radiation segmentectomy with fair to good accuracy and excellent positive predictive value. • There was no difference in diagnostic accuracy between mRECIST, LI-RADS, and subtraction for predicting HCC response to radiation segmentectomy.

Abbreviated MRI Protocols in the Abdomen and Pelvis.

Abbreviated MRI (AMRI) protocols rely on the acquisition of a limited number of sequences tailored to a specific question. The main objective of AMRI protocols is to reduce exam duration and costs, while maintaining an acceptable diagnostic performance. AMRI is of increasing interest in the radiology community; however, challenges limiting clinical adoption remain. In this review, we will address main abdominal and pelvic applications of AMRI in the liver, pancreas, kidney, and prostate, including diagnostic performance, pitfalls, limitations, and cost effectiveness will also be discussed. Level of Evidence: 3 Technical Efficacy Stage: 3.

MR Enterography in Ulcerative Colitis: Beyond Endoscopy.

Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease (IBD) that progressively affects mucosa and submuccosa of the colon and rectum in a continual pattern. In comparison, Crohn disease (CD), the other type of IBD, is a chronic transmural inflammatory disorder that can involve any part of the gastrointestinal tract. MR enterography (MRE) has emerged as an important imaging modality for the diagnosis and detection of disease activity and complications in CD, with comparable results to those of endoscopy. But MRE has been underused for assessment of UC in recent years, and clinicians heavily rely on endoscopic findings for management of UC. Despite UC being considered an endoscopically assessable disease, MRE can provide useful information beyond that obtained with endoscopy about mural or extramural abnormalities, inaccessible parts of the colonic lumen, associated extraintestinal diseases, and superimposed pathologic conditions. Moreover, endoscopy might be contraindicated in some clinical settings due to the risk of colonic perforation. In addition to depicting the features of UC activity in different phases, MRE demonstrates findings of disease chronicity that cannot be achieved with endoscopy, particularly in a patient with colitis of unknown cause. The valuable diagnostic role of MRE to exclude undiagnosed CD in patients with UC who have refractory disease or those with postproctocolectomy complications is also emphasized. Radiologists can play a crucial role in the management of UC with MRE by addressing what is beyond endoscopy. ©RSNA, 2023 Test Your Knowledge questions are available in the supplemental material.

Prediction of locally advanced rectal cancer response to neoadjuvant chemoradiation therapy using volumetric multiparametric MRI-based radiomics.

PURPOSE: To assess the role of pretreatment multiparametric (mp)MRI-based radiomic features in predicting pathologic complete response (pCR) of locally advanced rectal cancer (LARC) to neoadjuvant chemoradiation therapy (nCRT). METHODS: This was a retrospective dual-center study including 98 patients (M/F 77/21, mean age 60 years) with LARC who underwent pretreatment mpMRI followed by nCRT and total mesorectal excision or watch and wait. Fifty-eight patients from institution 1 constituted the training set and 40 from institution 2 the validation set. Manual segmentation using volumes of interest was performed on T1WI pre-/post-contrast, T2WI and diffusion-weighted imaging (DWI) sequences. Demographic information and serum carcinoembryonic antigen (CEA) levels were collected. Shape, 1st and 2nd order radiomic features were extracted and entered in models based on principal component analysis used to predict pCR. The best model was obtained using a k-fold cross-validation method on the training set, and AUC, sensitivity and specificity for prediction of pCR were calculated on the validation set. RESULTS: Stage distribution was T3 (n = 79) or T4 (n = 19). Overall, 16 (16.3%) patients achieved pCR. Demographics, MRI TNM stage, and CEA were not predictive of pCR (p range 0.59-0.96), while several radiomic models achieved high diagnostic performance for prediction of pCR (in the validation set), with AUCs ranging from 0.7 to 0.9, with the best model based on high b-value DWI demonstrating AUC of 0.9 [95% confidence intervals: 0.67, 1], sensitivity of 100% [100%, 100%], and specificity of 81% [66%, 96%]. CONCLUSION: Radiomic models obtained from pre-treatment MRI show good to excellent performance for the prediction of pCR in patients with LARC, superior to clinical parameters and CEA. A larger study is needed for confirmation of these results.

Benign and Malignant Ovarian Teratomas: Multimodality Imaging Findings With Histopathologic Correlation.

ABSTRACT: The purpose of this article is to provide a comprehensive review of the imaging findings along with histopathologic correlation of mature (benign) teratomas and malignant ovarian teratomas, which include both immature teratomas and malignant degeneration of mature teratomas. The radiologist's ability to provide an accurate diagnosis plays an essential role in guiding the interdisciplinary care of patients with malignant teratomas and improving their outcomes.