Symptoms Associated with Gadolinium Exposure (SAGE): A Suggested Term.

In this article, members of the American College of Radiology Committee on Drugs and Contrast Media propose a new term for symptoms reported after intravascular exposure to gadolinium-based contrast agents-Symptoms Associated with Gadolinium Exposure, or SAGE. This term is advocated in lieu of other proposed nomenclature that presumes a causal relationship that has not yet been scientifically verified. The purpose of this new term, SAGE, is to assist researchers and clinical providers in describing such symptoms without prematurely causally attributing them to a disease and to standardize reporting of these symptoms to allow for coherent interpretation of related studies.

Use of Intravenous Gadolinium-based Contrast Media in Patients with Kidney Disease: Consensus Statements from the American College of Radiology and the National Kidney Foundation.

Inaugural consensus statements were developed and endorsed by the American College of Radiology (ACR) and the National Kidney Foundation to improve and standardize the care of patients with kidney disease who have indication(s) to receive ACR-designated group II or group III intravenous gadolinium-based contrast media (GBCM). The risk of nephrogenic systemic fibrosis (NSF) from group II GBCM in patients with advanced kidney disease is thought to be very low (zero events following 4931 administrations to patients with estimated glomerular filtration rate [eGFR] <30 mL/min per 1.73 m2; upper bounds of the 95% confidence intervals: 0.07% overall, 0.2% for stage 5D chronic kidney disease [CKD], 0.5% for stage 5 CKD and no dialysis). No unconfounded cases of NSF have been reported for the only available group III GBCM (gadoxetate disodium). Depending on the clinical indication, the potential harms of delaying or withholding group II or group III GBCM for an MRI in a patient with acute kidney injury or eGFR less than 30 mL/min per 1.73 m2 should be balanced against and may outweigh the risk of NSF. Dialysis initiation or alteration is likely unnecessary based on group II or group III GBCM administration. This article is a simultaneous joint publication in Radiology and Kidney Medicine. The articles are identical except for stylistic changes in keeping with each journal's style. Either version may be used in citing this article.

The Prognostic Association of Prostate MRI PI-RADS™ v2 Assessment Category and Risk of Biochemical Recurrence after Definitive Local Therapy for Prostate Cancer: A Systematic Review and Meta-Analysis.

PURPOSE: Although the Prostate Imaging-Reporting and Data System™ version 2 (PI-RADS™ v2) is a reliable diagnostic tool for significant prostate cancer, less is known about the prognostic significance of the structured reporting scheme for estimating oncologic outcomes after treatment. We aimed to synthesize the available evidence regarding the association of PI-RADS v2 score and risk of biochemical recurrence (BCR) among patients undergoing primary definitive treatment for prostate cancer. MATERIALS AND METHODS: We systematically queried the PubMed® and Web of Science™ databases to identify studies addressing the association between the PI-RADS v2 and treatment outcomes. We included studies through November 2020 that assessed the independent prognostic significance of PI-RADS v2. After assessing risk of bias and quality, we conducted a formal meta-analysis to estimate the pooled effects of prostate magnetic resonance imaging (MRI) classification on the risk of BCR. RESULTS: We identified 9 and 7 eligible studies including 2,274 and 1,215 patients for the systematic review and meta-analysis, respectively. Eight were conducted in the context of radical prostatectomy and 1 post-radiation. Among patients treated with radical prostatectomy, higher PI-RADS v2 scores were significantly associated with risk of BCR (pooled HR 3.06, 95% CI 2.16-4.33; p <0.01). There was no significant heterogeneity among studies. For all studies, PI-RADS v2 score remained significantly associated with BCR (pooled HR 3.19, 95% CI 2.28-4.45; p <0.01). CONCLUSIONS: Prostate MRI findings assessed with the PI-RADS v2 classification were independently associated with risk of BCR after definitive local therapy, primarily based on data from radical prostatectomy. These findings support the prognostic significance of MRI, in addition to its role in prostate cancer diagnosis.

Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver.

OBJECTIVES: To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI. METHODS: This IRB-approved retrospective study included 118 patients with 150 lesions (93 (62%) HCC and 57 (38%) non-HCC) pathologically confirmed through biopsies (n = 72), resections (n = 29), liver transplants (n = 46), and autopsies (n = 3). Forty-seven percent of HCC lesions showed atypical imaging features (not meeting Liver Imaging Reporting and Data System [LI-RADS] criteria for definitive HCC/LR5). A 3D convolutional neural network (CNN) was trained on 140 lesions and tested for its ability to classify the 10 remaining lesions (5 HCC/5 non-HCC). Performance of the model was averaged over 150 runs with random sub-sampling to provide class-balanced test sets. A lesion grading system was developed to demonstrate the similarity between atypical HCC and non-HCC lesions prone to misclassification by the CNN. RESULTS: The CNN demonstrated an overall accuracy of 87.3%. Sensitivities/specificities for HCC and non-HCC lesions were 92.7%/82.0% and 82.0%/92.7%, respectively. The area under the receiver operating curve was 0.912. CNN's performance was correlated with the lesion grading system, becoming less accurate the more atypical imaging features the lesions showed. CONCLUSION: This study provides proof-of-concept for CNN-based classification of both typical- and atypical-appearing HCC lesions on multi-phasic MRI, utilizing pathologically confirmed lesions as "ground truth." KEY POINTS: • A CNN trained on atypical appearing pathologically proven HCC lesions not meeting LI-RADS criteria for definitive HCC (LR5) can correctly differentiate HCC lesions from other liver malignancies, potentially expanding the role of image-based diagnosis in primary liver cancer with atypical features. • The trained CNN demonstrated an overall accuracy of 87.3% and a computational time of < 3 ms which paves the way for clinical application as a decision support instrument.

PI-RADS Committee Position on MRI Without Contrast Medium in Biopsy-Naive Men With Suspected Prostate Cancer: Narrative Review.

The steadily increasing demand for diagnostic prostate MRI has led to concerns regarding the lack of access to and the availability of qualified MRI scanners and sufficiently experienced radiologists, radiographers, and technologists to meet the demand. Solutions must enhance operational benefits without compromising diagnostic performance, quality, and delivery of service. Solutions should also mitigate risks such as decreased reader confidence and referrer engagement. One approach may be the implementation of MRI without the use gadolinium-based contrast medium (bipara-metric MRI), but only if certain prerequisites such as high-quality imaging, expert interpretation quality, and availability of patient recall or on-table monitoring are mandated. Alternatively, or in combination, a clinical risk-based approach could be used for protocol selection, specifically, which biopsy-naive men need MRI with contrast medium (multiparametric MRI). There is a need for prospective studies in which biopsy decisions are made according to MRI without contrast enhancement. Such studies must define clinical and operational benefits and identify which patient groups can be scanned successfully without contrast enhancement. These higher-quality data are needed before the Prostate Imaging Reporting and Data System (PI-RADS) Committee can make evidence-based recommendations about MRI without contrast enhancement as an initial diagnostic approach for prostate cancer workup.

Use of Intravenous Iodinated Contrast Media in Patients with Kidney Disease: Consensus Statements from the American College of Radiology and the National Kidney Foundation.

Intravenous iodinated contrast media are commonly used with CT to evaluate disease and to determine treatment response. The risk of acute kidney injury (AKI) developing in patients with reduced kidney function following exposure to intravenous iodinated contrast media has been overstated. This is due primarily to historic lack of control groups sufficient to separate contrast-induced AKI (CI-AKI; ie, AKI caused by contrast media administration) from contrast-associated AKI (CA-AKI; ie, AKI coincident to contrast media administration). Although the true risk of CI-AKI remains uncertain for patients with severe kidney disease, prophylaxis with intravenous normal saline is indicated for patients who have AKI or an estimated glomerular filtration rate less than 30 mL/min/1.73 m2 who are not undergoing maintenance dialysis. In individual high-risk circumstances, prophylaxis may be considered in patients with an estimated glomerular filtration rate of 30-44 mL/min/1.73 m2 at the discretion of the ordering clinician. This article is a simultaneous joint publication in Radiology and Kidney Medicine. The articles are identical except for stylistic changes in keeping with each journal's style. Either version may be used in citing this article.

ACR guidance document on MR safe practices: Updates and critical information 2019.

The need for a guidance document on MR safe practices arose from a growing awareness of the MR environment's potential risks and adverse event reports involving patients, equipment, and personnel. Initially published in 2002, the American College of Radiology White Paper on MR Safety established de facto industry standards for safe and responsible practices in clinical and research MR environments. The most recent version addresses new sources of risk of adverse events, increases awareness of dynamic MR environments, and recommends that those responsible for MR medical director safety undergo annual MR safety training. With regular updates to these guidelines, the latest MR safety concerns can be accounted for to ensure a safer MR environment where dangers are minimized. Level of Evidence: 1 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2020;51:331-338.

Gadolinium Deposition and Nephrogenic Systemic Fibrosis: A Radiologist's Primer.

Gadolinium-based contrast agents (GBCAs) have an excellent safety profile. However, over the last 2 decades, two specific concerns have surfaced. GBCAs are associated with nephrogenic systemic fibrosis (NSF) and tissue retention of gadolinium. NSF is a rare fibrosing disorder with a poor prognosis, which is characterized by skin and subcutaneous thickening as well as systemic manifestations. The disease has been reported exclusively in patients with advanced renal disease, and it is associated with higher doses and specific types of GBCAs. The number of new cases of NSF has fallen over the past decade, presumably because of adherence by health care providers to regulatory guidelines, which continue to evolve. While gadolinium retention has been known to occur in the liver and bones, the relatively recent findings of deposition and retention in the brain have reignited the debate concerning the safety profile of GBCAs. Despite these concerns, there have been no proven health effects related to gadolinium deposition and retention other than NSF. The authors review the different categories of GBCAs available for commercial use, discuss NSF and gadolinium retention in the brain, and provide updates on the latest U.S. and European regulatory guidelines regarding use of these agents. Given the frequency with which GBCAs are used in clinical practice, it is imperative for all radiologists to learn the current guidelines to provide the safest and highest quality of patient care. ©RSNA, 2019.

PI-RADS Steering Committee: The PI-RADS Multiparametric MRI and MRI-directed Biopsy Pathway.

High-quality evidence shows that MRI in biopsy-naive men can reduce the number of men who need prostate biopsy and can reduce the number of diagnoses of clinically insignificant cancers that are unlikely to cause harm. In men with prior negative biopsy results who remain under persistent suspicion, MRI improves the detection and localization of life-threatening prostate cancer with greater clinical utility than the current standard of care, systematic transrectal US-guided biopsy. Systematic analyses show that MRI-directed biopsy increases the effectiveness of the prostate cancer diagnosis pathway. The incorporation of MRI-directed pathways into clinical care guidelines in prostate cancer detection has begun. The widespread adoption of the Prostate Imaging Reporting and Data System (PI-RADS) for multiparametric MRI data acquisition, interpretation, and reporting has promoted these changes in practice. The PI-RADS MRI-directed biopsy pathway enables the delivery of key diagnostic benefits to men suspected of having cancer based on clinical suspicion. Herein, the PI-RADS Steering Committee discusses how the MRI pathway should be incorporated into routine clinical practice and the challenges in delivering the positive health impacts needed by men suspected of having clinically significant prostate cancer.

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features.

OBJECTIVES: To develop a proof-of-concept "interpretable" deep learning prototype that justifies aspects of its predictions from a pre-trained hepatic lesion classifier. METHODS: A convolutional neural network (CNN) was engineered and trained to classify six hepatic tumor entities using 494 lesions on multi-phasic MRI, described in Part 1. A subset of each lesion class was labeled with up to four key imaging features per lesion. A post hoc algorithm inferred the presence of these features in a test set of 60 lesions by analyzing activation patterns of the pre-trained CNN model. Feature maps were generated that highlight regions in the original image that correspond to particular features. Additionally, relevance scores were assigned to each identified feature, denoting the relative contribution of a feature to the predicted lesion classification. RESULTS: The interpretable deep learning system achieved 76.5% positive predictive value and 82.9% sensitivity in identifying the correct radiological features present in each test lesion. The model misclassified 12% of lesions. Incorrect features were found more often in misclassified lesions than correctly identified lesions (60.4% vs. 85.6%). Feature maps were consistent with original image voxels contributing to each imaging feature. Feature relevance scores tended to reflect the most prominent imaging criteria for each class. CONCLUSIONS: This interpretable deep learning system demonstrates proof of principle for illuminating portions of a pre-trained deep neural network's decision-making, by analyzing inner layers and automatically describing features contributing to predictions. KEY POINTS: • An interpretable deep learning system prototype can explain aspects of its decision-making by identifying relevant imaging features and showing where these features are found on an image, facilitating clinical translation. • By providing feedback on the importance of various radiological features in performing differential diagnosis, interpretable deep learning systems have the potential to interface with standardized reporting systems such as LI-RADS, validating ancillary features and improving clinical practicality. • An interpretable deep learning system could potentially add quantitative data to radiologic reports and serve radiologists with evidence-based decision support.

Deep learning for liver tumor diagnosis part I: development of a convolutional neural network classifier for multi-phasic MRI.

OBJECTIVES: To develop and validate a proof-of-concept convolutional neural network (CNN)-based deep learning system (DLS) that classifies common hepatic lesions on multi-phasic MRI. METHODS: A custom CNN was engineered by iteratively optimizing the network architecture and training cases, finally consisting of three convolutional layers with associated rectified linear units, two maximum pooling layers, and two fully connected layers. Four hundred ninety-four hepatic lesions with typical imaging features from six categories were utilized, divided into training (n = 434) and test (n = 60) sets. Established augmentation techniques were used to generate 43,400 training samples. An Adam optimizer was used for training. Monte Carlo cross-validation was performed. After model engineering was finalized, classification accuracy for the final CNN was compared with two board-certified radiologists on an identical unseen test set. RESULTS: The DLS demonstrated a 92% accuracy, a 92% sensitivity (Sn), and a 98% specificity (Sp). Test set performance in a single run of random unseen cases showed an average 90% Sn and 98% Sp. The average Sn/Sp on these same cases for radiologists was 82.5%/96.5%. Results showed a 90% Sn for classifying hepatocellular carcinoma (HCC) compared to 60%/70% for radiologists. For HCC classification, the true positive and false positive rates were 93.5% and 1.6%, respectively, with a receiver operating characteristic area under the curve of 0.992. Computation time per lesion was 5.6 ms. CONCLUSION: This preliminary deep learning study demonstrated feasibility for classifying lesions with typical imaging features from six common hepatic lesion types, motivating future studies with larger multi-institutional datasets and more complex imaging appearances. KEY POINTS: • Deep learning demonstrates high performance in the classification of liver lesions on volumetric multi-phasic MRI, showing potential as an eventual decision-support tool for radiologists. • Demonstrating a classification runtime of a few milliseconds per lesion, a deep learning system could be incorporated into the clinical workflow in a time-efficient manner.

Notice of Withdrawal: MR Imaging and Gadolinium: Reassessing the Risk of Nephrogenic Systemic Fibrosis in Patients with Severe Renal Disease.

This editorial has been withdrawn from publication by the authors in conjunction with the withdrawal of the highlighted manuscript (see https://doi.org/10.1148/radiol.2017170102).

Evolving Use of Prebiopsy Prostate Magnetic Resonance Imaging in the Medicare Population.

PURPOSE: We assessed the changing use of prebiopsy prostate magnetic resonance imaging in Medicare beneficiaries. MATERIALS AND METHODS: Men who underwent prostate biopsy were identified in 5% Medicare RIFs (Research Identifiable Files) from October 2010 through September 2015. We evaluated the rate of prebiopsy prostate magnetic resonance imaging, defined as any pelvic MRI 6 months or less before biopsy with a prostate indication diagnosis code. Temporal changes were determined as well as variation by geography and among populations. RESULTS: In male Medicare beneficiaries the prebiopsy magnetic resonance imaging use rate increased from 0.1% in 2010 to 0.7% in 2011, to 1.2% in 2012, to 2.9% in 2013, to 4.7% in 2014 and to 10.3% in 2015. In 2015 the prebiopsy prostate magnetic resonance imaging rate varied significantly by patient age, including 5.7% for greater than 80 years vs 8.4% to 9.3% for other age ranges (p = 0.040) as well as by race, including 5.8% in African American vs 10.1% in Caucasian men (p = 0.009) and geographic region, including 6.3% in the Midwest to 12.5% in the Northeast (p <0.001). The rate was highest in Wyoming at 25.0%, New York at 23.7% and Minnesota at 20.5% but it was less than 1% in 10 states. CONCLUSIONS: Historical Medicare claims provide novel insights into the dramatically increasing adoption of magnetic resonance imaging prior to prostate biopsy. Following earlier minimal use the performance increased sharply beginning in 2013, exceeding 10% in 2015. However, substantial racial and geographic variation exists in adoption. Continued educational, research and policy efforts are warranted to optimize the role of prebiopsy magnetic resonance imaging and minimize sociodemographic and geographic disparities.

Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.

OBJECTIVE: The objective of this study is to determine the frequency of clinically significant cancer (CSC) in Prostate Imaging Reporting and Data System (PI-RADS) category 3 (equivocal) lesions prospectively identified on multiparametric prostate MRI and to identify risk factors (RFs) for CSC that may aid in decision making. MATERIALS AND METHODS: Between January 2015 and July 2016, a total of 977 consecutively seen men underwent multiparametric prostate MRI, and 342 underwent MRI-ultrasound (US) fusion targeted biopsy. A total of 474 lesions were retrospectively reviewed, and 111 were scored as PI-RADS category 3 and were visualized using a 3-T MRI scanner. Multiparametric prostate MR images were prospectively interpreted by body subspecialty radiologists trained to use PI-RADS version 2. CSC was defined as a Gleason score of at least 7 on targeted biopsy. A multivariate logistic regression model was constructed to identify the RFs associated with CSC. RESULTS: Of the 111 PI-RADS category 3 lesions, 81 (73.0%) were benign, 11 (9.9%) were clinically insignificant (Gleason score, 6), and 19 (17.1%) were clinically significant. On multivariate analysis, three RFs were identified as significant predictors of CSC: older patient age (odds ratio [OR], 1.13; p = 0.002), smaller prostate volume (OR, 0.94; p = 0.008), and abnormal digital rectal examination (DRE) findings (OR, 3.92; p = 0.03). For PI-RADS category 3 lesions associated with zero, one, two, or three RFs, the risk of CSC was 4%, 16%, 62%, and 100%, respectively. PI-RADS category 3 lesions for which two or more RFs were noted (e.g., age ≥ 70 years, gland size ≤ 36 mL, or abnormal DRE findings) had a CSC detection rate of 67% with a sensitivity of 53%, a specificity of 95%, a positive predictive value of 67%, and a negative predictive value of 91%. CONCLUSION: Incorporating clinical parameters into risk stratification algorithms may improve the ability to detect clinically significant disease among PI-RADS category 3 lesions and may aid in the decision to perform biopsy.

MRI-Ultrasound Fusion Targeted Biopsy of Prostate Imaging Reporting and Data System Version 2 Category 5 Lesions Found False-Positive at Multiparametric Prostate MRI.

OBJECTIVE: The purpose of this study was to determine imaging and clinical features associated with Prostate Imaging Reporting and Data System (PI-RADS) category 5 lesions identified prospectively at multiparametric MRI (mpMRI) that were found benign at MRI-ultrasound fusion targeted biopsy. MATERIALS AND METHODS: Between January 2015 and July 2016, 325 men underwent prostate mpMRI followed by MRI-ultrasound fusion targeted biopsy of 420 lesions prospectively identified and assessed with PI-RADS version 2. The frequency of clinically significant prostate cancer (defined as Gleason score ≥ 7) among PI-RADS 5 lesions was determined. Lesions with benign pathologic results were retrospectively reassessed by three abdominal radiologists and categorized as concordant or discordant between mpMRI and biopsy results. Multivariate logistic regression was used to identify factors associated with benign disease. Bonferroni correction was used. RESULTS: Of the 98 PI-RADS 5 lesions identified in 89 patients, 18% (18/98) were benign, 10% (10/98) were Gleason 6 disease, and 71% (70/98) were clinically significant prostate cancer. Factors associated with benign disease at multivariate analysis were lower prostate-specific antigen density (odds ratio [OR], 0.88; p < 0.001) and apex (OR, 3.54; p = 0.001) or base (OR, 7.11; p = 0.012) location. On secondary review of the 18 lesions with benign pathologic results, 39% (7/18) were scored as benign prostatic hyperplasia nodules, 28% (5/18) as inflammatory changes, 5% (1/18) as normal anatomic structures, and 28% (5/18) as discordant with imaging findings. CONCLUSION: PI-RADS 5 lesions identified during routine clinical interpretation are associated with a high risk of clinically significant prostate cancer. A benign pathologic result was significantly correlated with lower prostate-specific antigen density and apex or base location and most commonly attributed to a benign prostatic hyperplasia nodule. Integration of these clinical features may improve the interpretation of high-risk lesions identified with mpMRI.

Role of MRI in the Use of an Absorbable Hydrogel Spacer in Men Undergoing Radiation Therapy for Prostate Cancer: What the Radiologist Needs to Know.

OBJECTIVE: Hydrogel spacers have a novel role in the treatment of low- and intermediate-risk prostate cancer with dose-escalated radiation therapy. Given the growing number of patients undergoing treatment with radiation therapy, the use of hydrogel spacers is expected to increase. The purpose of this article is to review what a radiologist needs to know about the imaging of hydrogel spacers, including MRI technique and appearance on CT and MRI. CONCLUSION: MRI has a critical role in the evaluation of hydrogel spacer placement and is used to facilitate contouring by the radiation oncologist. The radiologist should be familiar with the imaging appearance of hydrogel spacers on CT and MRI to avoid interpretation pitfalls and errors.

PI-RADS Version 2: A Pictorial Update.

The Prostate Imaging Reporting and Data System (PI-RADS) is the result of an extensive international collaborative effort. PI-RADS provides a comprehensive yet practical set of guidelines for the interpretation and reporting of prostate multiparametric magnetic resonance (MR) imaging that will promote the use of this modality for detecting clinically significant prostate cancer. The revised PI-RADS version (PI-RADS version 2) introduces important changes to the original system used for assessing the level of suspicion for clinically significant cancer with multiparametric MR imaging. For peripheral zone abnormalities in PI-RADS version 2, the score obtained from the apparent diffusion coefficient (ADC) map in combination with diffusion-weighted imaging (DWI) performed with high b values (≥1400 sec/mm(2)) is the dominant parameter for determining the overall level of suspicion for clinically significant cancer. For transition zone abnormalities, the score obtained from T2-weighted MR imaging is dominant for overall lesion assessment. Dynamic contrast material-enhanced MR imaging has ancillary roles in the characterization of peripheral zone lesions considered equivocal for clinically significant cancer on the basis of the DWI-ADC combination and in the detection of lesions missed with other multiparametric MR pulse sequences. Assessment with dynamic contrast-enhanced MR imaging is also simplified, being considered positive or negative on the basis of qualitative evaluation for a focal area of rapid enhancement matching an abnormality on DWI-ADC or T2-weighted MR images. In PI-RADS version 2, MR spectroscopic imaging is not incorporated into lesion assessment. In this article, a pictorial overview is provided of the revised PI-RADS version 2 assessment categories for the likelihood of clinically significant cancer. PI-RADS version 2 is expected to evolve with time, with updated versions being released as experience in the use of PI-RADS version 2 increases and as new scientific evidence and technologies emerge. (©)RSNA, 2016.