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Background A preoperative predictive model is needed that can be used to identify patients with lung adenocarcinoma (LUAD) who have a higher risk of recurrence or metastasis. Purpose To investigate associations between CT-based radiomic consensus clustering of stage I LUAD and clinical-pathologic features, genomic data, and patient outcomes. Materials and Methods Patients who underwent complete surgical resection for LUAD from April 2014 to December 2017 with preoperative CT and next-generation sequencing data were retrospectively identified. Comprehensive radiomic analysis was performed on preoperative CT images; tumors were classified as solid, ground glass, or mixed. Patients were clustered into groups based on their radiomics features using consensus clustering, and clusters were compared with tumor genomic alterations, histopathologic features, and recurrence-specific survival (Kruskal-Wallis test for continuous data, χ

Opportunistic CT screening leverages robust imaging data embedded within abdominal and thoracic scans that are generally unrelated to the specific clinical indication and have heretofore gone largely unused. This incidental imaging information may prove beneficial to patients in terms of wellness, prevention, risk profiling, and presymptomatic detection of relevant disease. The growing interest in CT-based opportunistic screening relates to a confluence of factors: the objective and generalizable nature of CT-based body composition measures, the emergence of fully automated explainable AI solutions, the sheer volume of body CT scans performed, and the increasing emphasis on precision medicine and value-added initiatives. With a systematic approach to body composition and other useful CT markers, initial evidence suggests that their ability to help radiologists assess biologic age and predict future adverse cardiometabolic events rivals even the best available clinical reference standards. Emerging data suggest that standalone “intended” CT screening over an unorganized opportunistic approach may be justified, especially when combined with established cancer screening. This review will discuss the current status of opportunistic CT screening, including specific body composition markers and the various disease processes that may be impacted. The remaining hurdles to widespread clinical adoption include generalization to more diverse patient populations, disparate technical settings, and reimbursement. © RSNA, 2022 An earlier incorrect version appeared online. This article was corrected on March 18, 2022.

Background In acute ischemic stroke (AIS), fluid-attenuated inversion recovery (FLAIR) is used for treatment decisions when onset time is unknown. Synthetic FLAIR could be generated with deep learning from information embedded in diffusion-weighted imaging (DWI) and could replace acquired FLAIR sequence (real FLAIR) and shorten MRI duration. Purpose To compare performance of synthetic and real FLAIR for DWI-FLAIR mismatch estimation and identification of patients presenting within 4.5 hours from symptom onset. Materials and Methods In this retrospective study, all pretreatment and early follow-up (48 hours after symptom onset) MRI data sets including DWI (

Background MR spectroscopic imaging (MRSI) allows in vivo assessment of brain metabolism and is of special interest in multiple sclerosis (MS), where morphologic MRI cannot depict major parts of disease activity. Purpose To evaluate the ability of 7.0-T MRSI to depict and visualize pathologic alterations in the normal-appearing white matter (NAWM) and cortical gray matter (CGM) in participants with MS and to investigate their relation to disability. Materials and Methods Free-induction decay MRSI was performed at 7.0 T. Participants with MS and age- and sex-matched healthy controls were recruited prospectively between January 2016 and December 2017. Metabolic ratios were obtained in white matter lesions, NAWM, and CGM regions. Subgroup analysis for MS-related disability based on Expanded Disability Status Scale (EDSS) scores was performed using analysis of covariance. Partial correlations were applied to explore associations between metabolic ratios and disability. Results Sixty-five participants with MS (mean age ± standard deviation, 34 years ± 9; 34 women) and 20 age- and sex-matched healthy controls (mean age, 32 years ± 7; 11 women) were evaluated. Higher signal intensity of myo-inositol (mI) with and without reduced signal intensity of

Background Acute chest pain with mild troponin rise and inconclusive diagnosis after clinical evaluation represents a diagnostic challenge. Triple-rule-out (TRO) CT may exclude coronary artery disease (CAD), as well as acute aortic syndrome and pulmonary embolism, but cannot help identify other causes of myocardial injury. Purpose To investigate the diagnostic value of a comprehensive CT protocol including both an angiographic and a late contrast enhancement (LCE) scan in participants with troponin-positive acute chest pain. Materials and Methods In this prospective study, consecutive patients with troponin-positive acute chest pain or anginal equivalent and inconclusive diagnosis after clinical evaluation (symptoms, markers, electrocardiography, and echocardiography) who underwent TRO CT between June 2018 and September 2020 were enrolled. TRO CT was performed to evaluate the presence of obstructive CAD (stenosis ≥50%), acute aortic syndrome, and pulmonary embolism. If the findings on the TRO CT scan were negative, an LCE CT scan was acquired after 10 minutes to assess the presence and pattern of scar and quantify the myocardial extracellular volume fraction. CT-based diagnoses were compared with diagnoses obtained with reference standard methods, including invasive coronary angiography, cardiac MRI, and endomyocardial biopsy. Results Eighty-four patients (median age, 69 years [interquartile range, 50-77 years]; 45 men) were enrolled. TRO CT helped identify obstructive CAD in 35 participants (42%), acute aortic syndrome in one (1.2%), and pulmonary embolism in six (7.1%). LCE CT scans were acquired in the remaining 42 participants. The following diagnoses were reached with use of LCE CT: myocarditis (22 of 42 participants [52%]), takotsubo cardiomyopathy (four of 42 [10%]), amyloidosis (three of 42 [7.1%]), myocardial infarction with nonobstructed coronary arteries (three of 42 [7.1%]), dilated cardiomyopathy (two of 42 [4.8%]), and negative or inconclusive findings (eight of 42 [19%]). The addition of LCE CT improved the diagnostic rate of TRO CT from 42 of 84 participants (50% [95% CI: 38.9, 61.1]) to 76 of 84 (90% [95% CI: 82.1, 95.8]) (

Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ

The widespread use of cross-sectional imaging has led to a continuous increase in the number of incidentally detected indeterminate renal masses. Frequently, these clinical scenarios involve an older patient with comorbidities and a small renal mass (≤4 cm). Despite aggressive treatment in early stages of the disease, a clear positive effect in reducing kidney cancer–specific mortality is lacking, indicating that many renal cancers exhibit an indolent oncologic behavior. Furthermore, in general, one in five small renal masses is histologically benign and may not benefit from aggressive treatment. Although active surveillance is increasingly recognized as a management option for some patients, the absence of reliable clinical and imaging predictive biologic markers of aggressiveness can contribute to patient anxiety and limit its use in clinical practice. A standardized approach to the image interpretation of solid renal masses has not been broadly implemented. The clear cell likelihood score (ccLS) derived from multiparametric MRI is useful in noninvasively identifying the clear cell subtype, the most common and aggressive form of kidney cancer. Herein, a review of the ccLS is presented, including a step-by-step guide for image interpretation and additional guidance for its implementation in clinical practice. © RSNA, 2021 Online supplemental material is available for this article.

Ductal carcinoma in situ (DCIS) is a nonobligate precursor of invasive cancer, and its detection, diagnosis, and management are controversial. DCIS incidence grew with the expansion of screening mammography programs in the 1980s and 1990s, and DCIS is viewed as a major driver of overdiagnosis and overtreatment. For pathologists, the diagnosis and classification of DCIS is challenging due to undersampling and interobserver variability. Understanding the progression from normal breast tissue to DCIS and, ultimately, to invasive cancer is limited by a paucity of natural history data with multiple proposed evolutionary models of DCIS initiation and progression. Although radiologists are familiar with the classic presentation of DCIS as asymptomatic calcifications at mammography, the expanded pool of modalities, advanced imaging techniques, and image analytics have identified multiple potential biomarkers of histopathologic characteristics and prognosis. Finally, there is growing interest in the nonsurgical management of DCIS, including active surveillance, to reduce overtreatment and provide patients with more personalized management options. However, current biomarkers are not adept at enabling identification of occult invasive disease at biopsy or accurately predicting the risk of progression to invasive disease. Several active surveillance trials are ongoing and are expected to better identify women with low-risk DCIS who may avoid surgery. © RSNA, 2021

Background Integrated PET/MRI is a promising modality for breast assessment. The most frequently used tracer, fluorine 18 (

The clinical importance of interstitial lung abnormality (ILA) is increasingly recognized. In July 2020, the Fleischner Society published a position paper about ILA. The purposes of this article are to summarize the definition, existing evidence, clinical management, and unresolved issues for ILA from a radiologic standpoint and to provide a practical guide for radiologists. ILA is a common incidental finding at CT and is often progressive and associated with worsened clinical outcomes. The hazard ratios for mortality range from 1.3 to 2.7 in large cohorts. Risk factors for ILA include age, smoking status, other inhalational exposures, and genetic factors (eg, gene encoding mucin 5B variant). Radiologists should systematically record the presence, morphologic characteristics, distribution, and subcategories of ILA (ie, nonsubpleural, subpleural nonfibrotic, and subpleural fibrotic), as these are informative for predicting progression and mortality. Clinically significant interstitial lung disease should not be considered ILA. Individuals with ILA are triaged into higher- and lower-risk groups depending on their risk factors for progression, and systematic follow-up, including CT, should be considered for the higher-risk group. Artificial intelligence-based automated analysis for ILA may be helpful, but further validation and improvement are needed. Radiologists have a central role in clinical management and research on ILA. © RSNA, 2021 Online supplemental material is available for this article.

Imaging has been a critical component of multiple sclerosis (MS) management for nearly 40 years. The visual information derived from structural MRI, that is, signs of blood-brain barrier disruption, inflammation and demyelination, and brain and spinal cord atrophy, are the primary metrics used to evaluate therapeutic efficacy in MS. The development of targeted imaging probes has expanded our ability to evaluate and monitor MS and its therapies at the molecular level. Most molecular imaging probes evaluated for MS applications are small molecules initially developed for PET, nearly half of which are derived from U.S. Food and Drug Administration–approved drugs and those currently undergoing clinical trials. Superparamagnetic and fluorinated particles have been used for tracking circulating immune cells (in situ labeling) and immunosuppressive or remyelinating therapeutic stem cells (ex vivo labeling) clinically using proton (hydrogen 1 [(1)H]) and preclinically using fluorine 19 ((19)F) MRI. Translocator protein PET and (1)H MR spectroscopy have been demonstrated to complement imaging metrics from structural (gadolinium-enhanced) MRI in nine and six trials for MS disease-modifying therapies, respectively. Still, despite multiple demonstrations of the utility of molecular imaging probes to evaluate the target location and to elucidate the mechanisms of disease-modifying therapies for MS applications, their use has been sparse in both preclinical and clinical settings. © RSNA, 2022

Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77

Contrast-enhanced mammography (CEM) has emerged as a viable alternative to contrast-enhanced breast MRI, and it may increase access to vascular imaging while reducing examination cost. Intravenous iodinated contrast materials are used in CEM to enhance the visualization of tumor neovascularity. After injection, imaging is performed with dual-energy digital mammography, which helps provide a low-energy image and a recombined or iodine image that depict enhancing lesions in the breast. CEM has been demonstrated to help improve accuracy compared with digital mammography and US in women with abnormal screening mammographic findings or symptoms of breast cancer. It has also been demonstrated to approach the accuracy of breast MRI in preoperative staging of patients with breast cancer and in monitoring response after neoadjuvant chemotherapy. There are early encouraging results from trials evaluating CEM in the screening of women who are at an increased risk of breast cancer. Although CEM is a promising tool, it slightly increases radiation dose and carries a small risk of adverse reactions to contrast materials. This review details the CEM technique, diagnostic and screening uses, and future applications, including artificial intelligence and radiomics. (C) RSNA, 2021

Background Although CT-based body composition (BC) metrics may inform disease risk and outcomes, obtaining these metrics has been too resource intensive for large-scale use. Thus, population-wide distributions of BC remain uncertain. Purpose To demonstrate the validity of fully automated, deep learning BC analysis from abdominal CT examinations, to define demographically adjusted BC reference curves, and to illustrate the advantage of use of these curves compared with standard methods, along with their biologic significance in predicting survival. Materials and Methods After external validation and equivalency testing with manual segmentation, a fully automated deep learning BC analysis pipeline was applied to a cross-sectional population cohort that included any outpatient without a cardiovascular disease or cancer who underwent abdominal CT examination at one of three hospitals in 2012. Demographically adjusted population reference curves were generated for each BC area. The

Radiation therapy (RT) continues to be one of the mainstays of cancer treatment. Considerable efforts have been recently devoted to integrating MRI into clinical RT planning and monitoring. This integration, known as MRI-guided RT, has been motivated by the superior soft-tissue contrast, organ motion visualization, and ability to monitor tumor and tissue physiologic changes provided by MRI compared with CT. Offline MRI is already used for treatment planning at many institutions. Furthermore, MRI-guided linear accelerator systems, allowing use of MRI during treatment, enable improved adaptation to anatomic changes between RT fractions compared with CT guidance. Efforts are underway to develop real-time MRI-guided intrafraction adaptive RT of tumors affected by motion and MRI-derived biomarkers to monitor treatment response and potentially adapt treatment to physiologic changes. These developments in MRI guidance provide the basis for a paradigm change in treatment planning, monitoring, and adaptation. Key challenges to advancing MRI-guided RT include real-time volumetric anatomic imaging, addressing image distortion because of magnetic field inhomogeneities, reproducible quantitative imaging across different MRI systems, and biologic validation of quantitative imaging. This review describes emerging innovations in offline and online MRI-guided RT, exciting opportunities they offer for advancing research and clinical care, hurdles to be overcome, and the need for multidisciplinary collaboration. (C) RSNA, 2020

Impending major hardware advances in cardiac CT include three areas: ultra-high-resolution (UHR) CT, photon-counting CT, and phase-contrast CT. Cardiac CT is a particularly demanding CT application that requires a high degree of temporal resolution, spatial resolution, and soft-tissue contrast in a moving structure. In this review, cardiac CT is used to highlight the strengths of these technical advances. UHR CT improves visualization of calcified and stented vessels but may result in increased noise and radiation exposure. Photon-counting CT uses multiple photon energies to reduce artifacts, improve contrast resolution, and perform material decomposition. Finally, phase-contrast CT uses x-ray refraction properties to improve spatial and soft-tissue contrast. This review describes these hardware advances in CT and their relevance to cardiovascular imaging. © RSNA, 2020

Background Anaplastic thyroid cancer (ATC) is aggressive with a poor prognosis, partly because of the immunosuppressive microenvironment created by tumor-associated macrophages (TAMs). Purpose To understand the relationship between TAM infiltration, tumor vascularization, and corresponding drug delivery by using ferumoxytol-enhanced MRI and macrin in an ATC mouse model. Materials and Methods ATC tumors were generated in 6-8-week-old female B6129SF1/J mice through intrathyroid injection to model orthotopic tumors, or intravenously to model hematogenous metastasis, and prospectively enrolled randomly into treatment cohorts (

Background Diffusion-weighted imaging (DWI) shows promise in detecting and monitoring breast cancer, but standard spin-echo (SE) echo-planar DWI methods often have poor image quality and low spatial resolution. Proposed alternatives include readout-segmented (RS) echo-planar imaging and axially reformatted (AR)-simultaneous multislice (SMS) imaging. Purpose To compare the resolution and image quality of standard SE echo-planar imaging DWI with two high-spatial-resolution alternatives, RS echo-planar and AR-SMS imaging, for breast imaging. Materials and Methods In a prospective study (2016-2018), three 5-minute DWI protocols were acquired at 3.0 T, including standard SE echo-planar imaging, RS echo-planar imaging with five segments, and AR-SMS imaging with four times slice acceleration. Participants were women undergoing breast MRI either as part of a treatment response clinical trial or undergoing breast MRI for screening or suspected cancer. A commercial breast phantom was imaged for resolution comparison. Three breast radiologists reviewed images in random order, including clinical images indicating the lesion, images with

Background Recently developed time-dependent diffusion MRI has potential in characterizing cellular tissue microstructures; however, its value in imaging prostate cancer (PCa) remains unknown. Purpose To investigate the feasibility of time-dependent diffusion MRI-based microstructural mapping for noninvasively characterizing cellular properties of PCa and for discriminating between clinically significant PCa and clinically insignificant disease. Materials and Methods Men with a clinical suspicion of PCa were enrolled prospectively between October 2019 and August 2020. Time-dependent diffusion MRI data were acquired with pulsed and oscillating gradient diffusion MRI sequences at an equivalent diffusion time of 7.5-30 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction, cellularity, and diffusivities, were estimated with a two-compartment model. These were compared for different International Society of Urological Pathology grade groups (GGs), and their performance in discriminating clinically significant PCa (GG1) from clinically insignificant disease (benign and GG 1) was determined with a linear discriminant analysis. The fitted microstructural parameters were validated by means of correlation with histopathologic measurements. Results In the 48 enrolled men, the time-dependent diffusion MRI measurements showed that higher GG was correlated with higher intracellular volume fraction and higher cellularity (intracellular volume fraction = 0.22, 0.36, 0.34, 0.37, and 0.40 in GGs 1-5, respectively

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at

MRI is a valuable clinical and research tool for patients undergoing deep brain stimulation (DBS). However, risks associated with imaging DBS devices have led to stringent regulations, limiting the clinical and research utility of MRI in these patients. The main risks in patients with DBS devices undergoing MRI are heating at the electrode tips, induced currents, implantable pulse generator dysfunction, and mechanical forces. Phantom model studies indicate that electrode tip heating remains the most serious risk for modern DBS devices. The absence of adverse events in patients imaged under DBS vendor guidelines for MRI demonstrates the general safety of MRI for patients with DBS devices. Moreover, recent work indicates that—given adequate safety data—patients may be imaged outside these guidelines. At present, investigators are primarily focused on improving DBS device and MRI safety through the development of tools, including safety simulation models. Existing guidelines provide a standardized framework for performing safe MRI in patients with DBS devices. It also highlights the possibility of expanding MRI as a tool for research and clinical care in these patients going forward. © RSNA, 2020 Online supplemental material is available for this article.

MRI plays an important role as a secondary test or problem-solving modality in the evaluation of adnexal lesions depicted at US. MRI has increased specificity compared with US, decreasing the number of false-positive diagnoses for malignancy and thereby avoiding unnecessary or over-extensive surgery in patients with benign lesions or borderline tumors, while women with possible malignancies can be expeditiously referred for oncologic surgical evaluation. The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee is an international collaborative effort formed under the direction of the American College of Radiology and includes a diverse group of experts on adnexal imaging and management who developed the O-RADS MRI risk stratification system. This scoring system assigns a probability of malignancy based on the MRI features of an adnexal lesion and provides information to facilitate optimal patient management. The widespread implementation of a codified reporting system will lead to improved interpretation agreement and standardized communication between radiologists and referring physicians. In addition, it will allow for high-quality multi-institutional collaborations—an important unmet need that has hampered the performance of high-quality research in this area in the past. This article provides guidelines on using the O-RADS MRI risk stratification system in clinical practice, as well as in the educational and research settings. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Levine in this issue.

Background In the Dutch breast cancer screening program, mammograms are preread by technologists to identify possible abnormalities, leading to "warning signals" (an audible and visual alert if the technologist observed an abnormality suspicious for cancer) for radiologists. The best moment to present these warning signals is unknown. Purpose To determine the effect that blinding of technologists' warning signals has on radiologists' early screening outcome measures during interpretation of mammograms. Materials and Methods In this prospective study from September 2017 to May 2019, on alternating months, radiologists were either blinded or nonblinded to the warning signals of the technologist when interpreting screening mammograms for breast cancer. All discrepancies between radiologists and technologists were reviewed during quality assurance sessions every 6 weeks, which could result in secondary recalls. The outcome measures of this study were recall rate, cancer detection rate, and positive predictive value of recall. A χ

Diffusion-weighted (DW) MRI is a rapid technique that measures the mobility of water molecules within tissue, reflecting the cellular microenvironment. At DW MRI, breast cancers typically exhibit reduced diffusivity and appear hyperintense to surrounding tissues. On the basis of this characteristic, DW MRI may offer an unenhanced method to detect breast cancer without the costs and safety concerns associated with dynamic contrast material–enhanced MRI, the current reference standard in the setting of high-risk screening. This application of DW MRI has not been widely explored but is particularly timely given the growing health concerns related to the long-term use of gadolinium-based contrast material. Moreover, increasing breast density notification legislation across the United States is raising awareness of the limitations of mammography in women with dense breasts, emphasizing the need for additional cost-effective supplemental screening examinations. Preliminary studies suggest unenhanced MRI with DW MRI may provide higher sensitivity than screening mammography for the detection of breast malignancies. Larger prospective multicenter trials are needed to validate single-center findings and assess the performance of DW MRI for generalized breast cancer screening. Standardization of DW MRI acquisition and interpretation is essential to ensure reliable sensitivity and specificity, and an optimal approach for screening using readily available techniques is proposed here. © RSNA, 2019 Online supplemental material is available for this article.

Background Missed fractures are a common cause of diagnostic discrepancy between initial radiographic interpretation and the final read by board-certified radiologists. Purpose To assess the effect of assistance by artificial intelligence (AI) on diagnostic performances of physicians for fractures on radiographs. Materials and Methods This retrospective diagnostic study used the multi-reader, multi-case methodology based on an external multicenter data set of 480 examinations with at least 60 examinations per body region (foot and ankle, knee and leg, hip and pelvis, hand and wrist, elbow and arm, shoulder and clavicle, rib cage, and thoracolumbar spine) between July 2020 and January 2021. Fracture prevalence was set at 50%. The ground truth was determined by two musculoskeletal radiologists, with discrepancies solved by a third. Twenty-four readers (radiologists, orthopedists, emergency physicians, physician assistants, rheumatologists, family physicians) were presented the whole validation data set (

Background Chimeric antigen receptor (CAR) T-cell immunotherapy is increasingly used for refractory lymphoma but may lead to cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Imaging may assist in clinical management. Associations between CRS or ICANS grade and imaging findings remain not fully established. Purpose To determine associations between imaging findings and clinical grade of CRS or ICANS, evaluate response patterns, and assess imaging use following CAR T-cell treatment. Materials and Methods Patients with refractory B-cell lymphoma who received CAR T-cell infusion between 2018 and 2020 at a single center were analyzed retrospectively. Clinical CRS or ICANS toxicity grade was assessed using American Society for Transplantation and Cellular Therapy, or ASTCT, consensus grading. Thoracic and head images (radiographs, CT scans, MRI scans) were evaluated. Associations between imaging findings and clinical CRS or ICANS grade were analyzed. Wilcoxon signed-rank and χ

Background Radiomics-based biomarkers enable the prognostication of resected non-small cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA pure-solid tumors requires further determination. Purpose To construct an efficient radiomics signature for survival risk stratification personalized for patients with clinical stage and pathologic stage IA pure-solid NSCLC. Materials and Methods In this retrospective study, six radiomics signatures were constructed for patients with stage IA pure-solid NSCLC who underwent resection between January 2011 and December 2013 at authors' institution and were tested in the radiogenomics data set. The radiomics features were extracted from the intratumoral two-dimensional region, three-dimensional volume, and peritumoral area using PyRadiomics. The discriminative abilities of the signatures were quantified using the area under the time-dependent receiver operating characteristic curve (AUC), and the optimal signature was selected for patient stratification. Results The study included 592 patients with stage IA pure-solid NSCLC (median age, 61 years; interquartile range, 55-66 years; 269 women) for radiomics analysis: 381 patients for training, 163 for internal validation, and 48 for external validation. The radiomics signature combining three-region features yielded the highest 3- and 5-year AUCs of 0.77 and 0.78, respectively, in the internal validation set and 0.76 and 0.75, respectively, in the external validation set. Multivariable analysis suggested that the radiomics signature remained an independent prognostic factor (hazard ratio, 6.2; 95% CI: 3.5, 11.0

Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift–encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation. © RSNA, 2021 Online supplemental material is available for this article.

BACKGROUND: Current imaging methods for prediction of complete margin resection (R0) in patients with pancreatic ductal adenocarcinoma (PDAC) are not reliable. PURPOSE: To investigate whether tumor-related and perivascular CT radiomic features improve preoperative assessment of arterial involvement in patients with surgically proven PDAC. MATERIALS AND METHODS: This retrospective study included consecutive patients with PDAC who underwent surgery after preoperative CT between 2012 and 2019. A three-dimensional segmentation of PDAC and perivascular tissue surrounding the superior mesenteric artery (SMA) was performed on preoperative CT images with radiomic features extracted to characterize morphology, intensity, texture, and task-based spatial information. The reference standard was the pathologic SMA margin status of the surgical sample: SMA involved (tumor cells ≤1 mm from margin) versus SMA not involved (tumor cells >1 mm from margin). The preoperative assessment of SMA involvement by a fellowship-trained radiologist in multidisciplinary consensus was the comparison. High reproducibility (intraclass correlation coefficient, 0.7) and the Kolmogorov-Smirnov test were used to select features included in the logistic regression model. RESULTS: A total of 194 patients (median age, 66 years; interquartile range, 60–71 years; age range, 36–85 years; 99 men) were evaluated. Aside from surgery, 148 patients underwent neoadjuvant therapy. A total of 141 patients’ samples did not involve SMA, whereas 53 involved SMA. A total of 1695 CT radiomic features were extracted. The model with five features (maximum hugging angle, maximum diameter, logarithm robust mean absolute deviation, minimum distance, square gray level co-occurrence matrix correlation) showed a better performance compared with the radiologist assessment (model vs radiologist area under the curve, 0.71 [95% CI: 0.62, 0.79] vs 0.54 [95% CI: 0.50, 0.59]; P < .001). The model showed a sensitivity of 62% (33 of 53 patients) (95% CI: 51, 77) and a specificity of 77% (108 of 141 patients) (95% CI: 60, 84). CONCLUSION: A model based on tumor-related and perivascular CT radiomic features improved the detection of superior mesenteric artery involvement in patients with pancreatic ductal adenocarcinoma.

Background Dual-energy CT enterography (DECTE) has been shown to be useful in characterizing Crohn disease activity compared with clinical markers of inflammation but, to the knowledge of the authors, comparison has not been made with histopathologic specimens. Purpose To compare mucosal iodine density obtained at DECTE from Crohn disease-affected bowel with histopathologic specimens from surgically resected ileocolectomy bowel segments or terminal ileum colonoscopic biopsies in the same patients. Materials and Methods This was a retrospective study. Bowel segments in adults with Crohn disease who underwent DECTE from January 2017 to April 2019 within 90 days of ileocolectomy or colonoscopy were retrospectively evaluated with prototype software allowing the semiautomatic determination of inner hyperdense bowel wall (mucosal) mean iodine density, normalized to the aorta. Mean normalized iodine density and clinical activity indexes (Crohn Disease Activity Index [CDAI] and Harvey-Bradshaw Index [HBI]) were compared with histologic active inflammation grades by using two-tailed

Background The bolus-tracking technique from single-energy CT has been applied to dual-energy CT (DECT) without optimization or validation. Further optimization is imperative because of a paucity of literature and differences in the attenuation profile of virtual monoenergetic images (VMIs). Purpose To determine the optimal trigger threshold with bolus-tracking technique for DECT angiography (DECTA) in a phantom study and assess the feasibility of an optimized threshold for bolus-tracking technique in DECTA at 40 keV with a 50% reduced iodine dose in human participants. Materials and Methods A phantom study with rapid kilovoltage-switching DECT was performed to determine the optimal threshold for each kiloelectron-volt VMI. In a prospective study, consecutive participants who underwent whole-body CT angiography (CTA) from August 2018 to July 2019 were randomized into three groups: single-energy CTA (SECTA) with standard iodine dose (600 mg of iodine per kilogram), DECTA with 50% reduced iodine dose (300 mg of iodine per kilogram) by using a conventional threshold, and DECTA with 300 mg of iodine per kilogram by using an optimized threshold. A trigger threshold of 100 HU at 120 kVp was used as a reference for comparison. Injected iodine doses and aortic CT numbers were compared among the three groups using Kruskal-Wallis test. Results Ninety-six participants (mean age ± standard deviation, 72 years ± 9; 80 men) were evaluated (32 participants in each group). The optimized threshold for VMIs at 40 keV was 30 HU. The median iodine dose was lower in the optimized DECTA group (13 g) compared with conventional DECTA (19 g) and SECTA (26 g) groups (

Background Despite known limitations, the decision to operate on abdominal aortic aneurysm (AAA) is primarily on the basis of measurement of maximal aneurysm diameter. Purpose To identify volumetric and computational fluid dynamics parameters to predict AAAs that are likely to progress in size. Materials and Methods This study, part of a multicenter prospective registry (NCT01599533), included 126 patients with AAA. Patients were sorted into stable (≤10-mL increase in aneurysm volume) and progression (10-mL increase in aneurysm volume) groups. Initial AAA characteristics of the derivation cohort were analyzed (maximal diameter and surface, thrombus and lumen volumes, maximal wall pressure, and wall shear stress [WSS]) to identify relevant parameters for a logistic regression model. Model and maximal diameter diagnostic performances were assessed in both cohorts and for AAAs smaller than 50 mm by using area under the receiver operating characteristic curve (AUC). Results Eighty-one patients were included (mean age, 73 years ± 7 years [standard deviation]; 78 men). The derivation and validation cohorts included, respectively, 50 and 31 participants. In the derivation cohort, there was higher mean lumen volume and lower mean WSS in the progression group compared with the stable group (60 mL ± 14 vs 46 mL ± 18 [

Background The role of preoperative MRI for predicting surgical outcomes in patients diagnosed with ductal carcinoma in situ (DCIS) remains uncertain. Purpose To investigate the associations between preoperative MRI and surgical outcomes in DCIS confirmed by using US-guided core-needle biopsy (CNB) and to evaluate clinical-pathologic variables associated with a benefit from MRI. Materials and Methods Women with DCIS confirmed by using US-guided CNB between January 2012 and December 2016 were included in this retrospective study. Propensity score matching using 18 confounding covariates was used to create matched groups with MRI and without MRI, and surgical outcomes were compared. Clinical-pathologic variables were evaluated to determine women who benefited from MRI. Results A total of 541 women (mean age ± standard deviation, 50 years ± 10) were evaluated. Among 430 women who underwent MRI, 67 additional lesions (16%) were depicted, with 25 (37%) of the 67 additional lesions being malignant. Fifty-seven (13%) of the 430 women had a change in surgical plan because of their MRI findings; the change was appropriate for 31 (54%) women. In matched groups, the MRI group was associated with lower odds of positive resection margin (odds ratio [OR], 0.39; 95% confidence interval [CI]: 0.16, 0.93

Background Pathologic evidence of Alzheimer disease (AD) is detectable years before onset of clinical symptoms. Imaging-based identification of structural changes of the brain in people at genetic risk for early-onset AD may provide insights into how genes influence the pathologic cascade that leads to dementia. Purpose To assess structural connectivity differences in cortical networks between cognitively normal autosomal dominant Alzheimer disease (ADAD) mutation carriers versus noncarriers and to determine the cross-sectional relationship of structural connectivity and cortical amyloid burden with estimated years to symptom onset (EYO) of dementia in carriers. Materials and Methods In this exploratory analysis of a prospective trial, all participants enrolled in the Dominantly Inherited Alzheimer Network between January 2009 and July 2014 who had normal cognition at baseline, T1-weighted MRI scans, and diffusion tensor imaging (DTI) were analyzed. Amyloid PET imaging using Pittsburgh compound B was also analyzed for mutation carriers. Areas of the cerebral cortex were parcellated into three cortical networks: the default mode network, frontoparietal control network, and ventral attention network. The structural connectivity of the three networks was calculated from DTI. General linear models were used to examine differences in structural connectivity between mutation carriers and noncarriers and the relationship between structural connectivity, amyloid burden, and EYO in mutation carriers. Correlation network analysis was performed to identify clusters of related clinical and imaging markers. Results There were 30 mutation carriers (mean age ± standard deviation, 34 years ± 10; 17 women) and 38 noncarriers (mean age, 37 years ± 10; 20 women). There was lower structural connectivity in the frontoparietal control network in mutation carriers compared with noncarriers (estimated effect of mutation-positive status, -0.0266

Background Four-dimensional (4D) flow MRI enables the evaluation of blood flow alterations in patients with congenital bicuspid aortic valve (BAV). However, current analysis methods are cumbersome and lack the use of the volumetric data from 4D MRI. Purpose To investigate the feasibility and reproducibility of a technique that uses a catheter-like mathematical model (virtual catheter) to assess volumetric intra-aortic hemodynamics from 4D flow MRI in patients with BAV. Materials and Methods In this retrospective study, data were collected from adult patients with BAV and healthy participants who underwent aortic 4D flow MRI from November 2011 through August 2014. Reproducibility was tested in healthy study participants who underwent test-retest examinations within 2 weeks. Patients were grouped on the basis of the severity of aortic valve regurgitation (AVR) and aortic valve stenosis (AVS). A 4D virtual catheter mathematical model for probing intra-aortic hemodynamic flow was constructed as a tube with an automatically derived radius along the entire thoracic aorta centerline. Volumetric intra-aortic hemodynamics were computed from 4D flow MRI only within the virtual catheter, and the following volume-normalized systolic peaks were derived: kinetic energy (KE), viscous energy loss rate (VELR), and vorticity. Hemodynamic data were presented as medians with interquartile ranges and compared by using Mann-Whitney

Background In patients who are expected to achieve axillary pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC), omission of axillary lymph node (LN) dissection could prevent morbidity and complications. Purpose To develop a clinical model to predict residual axillary LN metastasis in patients with clinically node-positive breast cancer after NAC by using MRI and US. Materials and Methods In this retrospective study, women with clinically node-positive breast cancer who were treated with NAC following surgery between January 2015 and September 2017 were included. The patients were randomly assigned to a test and validation set (7:3 ratio). Univariable and multivariable logistic regression analyses were performed to evaluate the independent predictors of residual axillary LN metastasis in the test set. A prediction risk score was developed based on the odds ratios from the multivariable analysis and validated in both sets. Results A total of 408 women were included (mean age ± standard deviation, 47.9 years ± 9.6). The axillary pCR rate was 56.6% (231 of 408). Independent predictors of residual axillary LN metastasis were clinical stage N2 or N3, presence of axillary lymphadenopathy at US after NAC, tumor size reduction less than 50% at MRI, Ki-67 negativity, hormone receptor positivity, and human epidermal growth factor receptor 2 negativity (all, P < .05). In a model using these predictors, the area under the receiver operating characteristic curve in the test and validation sets was 0.84 (95% confidence interval: 0.79, 0.88) and 0.78 (95% confidence interval: 0.70, 0.87), respectively. When the patients had a simplified risk score of 1, the false-negative rates ranged between 5%-10%. Conclusion A prediction model incorporating nodal status stage, US finding, MRI response, and molecular receptor status shows good diagnostic performance for residual axillary lymph node metastasis after neoadjuvant chemotherapy in patients with clinically node-positive breast cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Whitman in this issue.

Background Right ventricular ejection fraction (RVEF) is an independent predictor of death and adverse cardiovascular outcomes in patients with various cardiac conditions. Purpose To investigate whether RVEF, measured with cardiac MRI, is a predictor of appropriate shock or death in implantable cardioverter-defibrillator (ICD) recipients for primary and secondary prevention of sudden cardiac death. Materials and Methods This retrospective, multicenter, observational study included patients who underwent cardiac MRI before ICD implantation between January 2007 and May 2017. Right ventricular end-diastolic and end-systolic volumes and RVEF were measured with cardiac MRI. The primary end point was a composite of all-cause mortality or appropriate ICD shock. The secondary end point was all-cause mortality. The association between RVEF and primary and secondary outcomes was evaluated by using multivariable Cox regression analysis. Potential interactions were tested between primary prevention, ischemic cause, left ventricular ejection fraction (LVEF), and RVEF. Results Among 411 patients (mean age ± standard deviation, 60 years; 315 men) during a median follow-up of 63 months, 143 (35%) patients experienced an appropriate ICD shock or died. In univariable analysis, lower RVEF was associated with greater risks for appropriate ICD shock or death and for death alone (log-rank trend test

Purpose To investigate the accuracy of dynamic contrast material-enhanced (DCE) breast MRI for determining residual tumor size after neoadjuvant chemotherapy (NAC). Materials and Methods For this retrospective study, 487 consecutive women (mean age, 47.0 years ± 10.3 [standard deviation]; range, 24-78 years) underwent preoperative DCE MRI following NAC and subsequent surgeries between 2008 and 2011. Tumor size was measured at early-phase, conventional delayed-phase, and late delayed-phase MRI (90, 360, and 590 seconds after contrast material injection, respectively). At histopathologic examination, total tumor size (both invasive and in situ) and the size of invasive tumor alone were separately recorded. Absolute agreement between tumor size at MRI and histopathologic examination was assessed by using intraclass correlation coefficient (ICC) analysis. Factors affecting size discrepancy were assessed by using multiple linear regression analysis. Results Compared with tumor size at histopathologic examination, total tumor sizes showed higher agreement at conventional delayed-phase MRI than at early-phase MRI (ICC, 0.76 vs 0.56; P ˂ .001) and comparable agreement at conventional and late delayed-phase MRI (ICC, 0.76 vs 0.74; P = .55). Lobular histologic features and tumor subtype were independently associated with greater size discrepancy (P ˂ .001). Lobular cancers were underestimated in size compared with ductal cancers (mean size discrepancy, -2.8 cm ± 3.2 vs -0.3 cm ± 1.8; P = .004). Estrogen receptor-positive/human epidermal growth factor receptor 2 (HER2)-negative cancers were underestimated compared with HER2-positive cancers (-0.8 cm ± 2.0 vs -0.3 cm ± 1.7, P = .006) and triple-negative cancers (-0.8 cm ± 2.0 vs 0.3 cm ± 1.7, P ˂ .001). Conclusion Delayed-phase MRI is more accurate than early-phase MRI for evaluating residual breast tumor size after neoadjuvant chemotherapy. Lobular or estrogen receptor-positive/human epidermal growth factor receptor 2-negative cancers are underestimated in size at MRI compared with ductal or other subtypes. © RSNA, 2018 Online supplemental material is available for this article.

Pulmonary functional imaging may be defined as the regional quantification of lung function by using primarily CT, MRI, and nuclear medicine techniques. The distribution of pulmonary physiologic parameters, including ventilation, perfusion, gas exchange, and biomechanics, can be noninvasively mapped and measured throughout the lungs. This information is not accessible by using conventional pulmonary function tests, which measure total lung function without viewing the regional distribution. The latter is important because of the heterogeneous distribution of virtually all lung disorders. Moreover, techniques such as hyperpolarized xenon 129 and helium 3 MRI can probe lung physiologic structure and microstructure at the level of the alveolar-air and alveolar–red blood cell interface, which is well beyond the spatial resolution of other clinical methods. The opportunities, challenges, and current stage of clinical deployment of pulmonary functional imaging are reviewed, including applications to chronic obstructive pulmonary disease, asthma, interstitial lung disease, pulmonary embolism, and pulmonary hypertension. Among the challenges to the deployment of pulmonary functional imaging in routine clinical practice are the need for further validation, establishment of normal values, standardization of imaging acquisition and analysis, and evidence of patient outcomes benefit. When these challenges are addressed, it is anticipated that pulmonary functional imaging will have an expanding role in the evaluation and management of patients with lung disease. © RSNA, 2021 Online supplemental material is available for this article.

Background Rapid knee MRI using combined simultaneous multislice (SMS) technique and parallel imaging (PI) acceleration can add value through reduced acquisition time but requires validation of clinical efficacy. Purpose To evaluate the performance of clinical fourfold SMS-PI-accelerated, 5-minute, five-sequence, multicontrast knee MRI protocols compared with standard twofold PI-accelerated, 10-minute knee MRI protocols. Materials and Methods Adults with painful knee conditions were prospectively enrolled from April 2018 to October 2019. Participants underwent fourfold SMS-PI-accelerated, 5-minute, turbo spin-echo (TSE) knee MRI and standard-of-care twofold PI-accelerated, 10-minute, TSE knee MRI at either 1.5 T or 3.0 T. Three radiologists independently evaluated the knee MRI studies for meniscal, tendinous, ligamentous, and osseocartilaginous injuries. Statistical analyses included k-based intermethod agreements and diagnostic performance testing.

Over the past few decades, pulmonary imaging technologies have advanced from chest radiography and nuclear medicine methods to high-spatial-resolution or low-dose chest CT and MRI. It is currently possible to identify and measure pulmonary pathologic changes before these are obvious even to patients or depicted on conventional morphologic images. Here, key technological advances are described, including multiparametric CT image processing methods, inhaled hyperpolarized and fluorinated gas MRI, and four-dimensional free-breathing CT and MRI methods to measure regional ventilation, perfusion, gas exchange, and biomechanics. The basic anatomic and physiologic underpinnings of these pulmonary functional imaging techniques are explained. In addition, advances in image analysis and computational and artificial intelligence (machine learning) methods pertinent to functional lung imaging are discussed. The clinical applications of pulmonary functional imaging, including both the opportunities and challenges for clinical translation and deployment, will be discussed in part 2 of this review. Given the technical advances in these sophisticated imaging methods and the wealth of information they can provide, it is anticipated that pulmonary functional imaging will be increasingly used in the care of patients with lung disease. © RSNA, 2021 Online supplemental material is available for this article.

Background Conventional radiologic modalities perform poorly in the radiated rectum and are often unable to differentiate residual cancer from treatment scarring. Purpose To report the development and initial patient study of an imaging system comprising an endorectal coregistered photoacoustic (PA) microscopy (PAM) and US system paired with a convolution neural network (CNN) to assess the rectal cancer treatment response. Materials and Methods In this prospective study (ClinicalTrials.gov identifier NCT04339374), participants completed radiation and chemotherapy from September 2019 to September 2020 and images were obtained with the PAM/US system prior to surgery. Another group's colorectal specimens were studied ex vivo. The PAM/US system consisted of an endorectal imaging probe, a 1064-nm laser, and one US ring transducer. The PAM CNN and US CNN models were trained and validated to distinguish normal from malignant colorectal tissue using ex vivo and in vivo patient data. The PAM CNN and US CNN were then tested using additional in vivo patient data that had not been seen by the CNNs during training and validation. Results Twenty-two patients' ex vivo specimens and five patients' in vivo images (a total of 2693 US regions of interest [ROIs] and 2208 PA ROIs) were used for CNN training and validation. Data from five additional patients were used for testing. A total of 32 participants (mean age, 60 years; range, 35-89 years) were evaluated. Unique PAM imaging markers of the complete tumor response were found, specifically including recovery of normal submucosal vascular architecture within the treated tumor bed. The PAM CNN model captured this recovery process and correctly differentiated these changes from the residual tumor. The imaging system remained highly capable of differentiating tumor from normal tissue, achieving an area under the receiver operating characteristic curve of 0.98 (95% CI: 0.98, 0.99) for data from five participants. By comparison, the US CNN had an area under the receiver operating characteristic curve of 0.71 (95% CI: 0.70, 0.73). Conclusion An endorectal coregistered photoacoustic microscopy/US system paired with a convolutional neural network model showed high diagnostic performance in assessing the rectal cancer treatment response and demonstrated potential for optimizing posttreatment management. © RSNA, 2021

Infection by SARS-CoV-2 virus ranges from asymptomatic to severe and sometimes fatal disease, most frequently the result of acute lung injury. The role of imaging has evolved during the pandemic, initially with CT as alternative and possibly superior test compared to RT-PCR, to a more limited role based on specific indications. Several classification and reporting schemes were developed for chest imaging early during the pandemic for patients with suspected COVID-19 to aid in triage when the availability of RT-PCR testing was limited and its performance unclear. Interobserver agreement for categories with findings typical of COVID-19 and those suggesting an alternative diagnosis is high across multiple studies. Furthermore, some studies looking at the extent of lung involvement on chest radiography and CT showed correlations with critical illness and need for mechanical ventilation. In addition to pulmonary manifestations, cardiovascular complications such as thromboembolism and myocarditis have been ascribed to COVID-19, sometimes contributing to neurologic and abdominal manifestations. Finally, artificial intelligence has shown promise in both diagnosis and prognosis of COVID-19 pneumonia both with respect to radiography and CT.

The increasing prevalence of dementia worldwide places a high demand on healthcare providers to perform a diagnostic work-up in relatively early stages of the disease, given that the pathologic process usually begins decades before symptoms are evident. Structural imaging is recommended to rule out other disorders and can only provide diagnosis in a late stage with limited specificity. Where PET imaging previously focused on the spatial pattern of hypometabolism, the past decade has seen the development of novel tracers to demonstrate characteristic protein abnormalities. Molecular imaging using PET/SPECT is able to show amyloid and tau deposition in Alzheimer disease and dopamine depletion in parkinsonian disorders starting decades before symptom onset. Novel tracers for neuroinflammation and synaptic density are being developed to further unravel the molecular pathologic characteristics of dementia disorders. In this article, the authors review the current status of established and emerging PET tracers in a diagnostic setting and also their value as prognostic markers in research studies and outcome measures for clinical trials in Alzheimer disease.