The 50 most-cited articles in Radiology, 2021

Background Little is known about the long-term lung radiographic changes in patients who have recovered from coronavirus disease 2019 (COVID-19), especially those with severe disease. Purpose To prospectively assess pulmonary sequelae and explore the risk factors for fibrotic-like changes in the lung at 6-month follow-up chest CT of survivors of severe COVID-19 pneumonia. Materials and Methods A total of 114 patients (80 [70%] men; mean age, 54 years ± 12) were studied prospectively. Initial and follow-up CT scans were obtained a mean of 17 days ± 11 and 175 days ± 20, respectively, after symptom onset. Lung changes (opacification, consolidation, reticulation, and fibrotic-like changes) and CT extent scores (score per lobe, 0–5; maximum score, 25) were recorded. Participants were divided into two groups on the basis of their 6-month follow-up CT scan: those with CT evidence of fibrotic-like changes (traction bronchiectasis, parenchymal bands, and/or honeycombing) (group 1) and those without CT evidence of fibrotic-like changes (group 2). Between-group differences were assessed with…

Background The first clinical CT system to use photon-counting detector (PCD) technology has become available for patient care. Purpose To assess the technical performance of the PCD CT system with use of phantoms and representative participant examinations. Materials and Methods Institutional review board approval and written informed consent from four participants were obtained. Technical performance of a dual-source PCD CT system was measured for standard and high-spatial-resolution (HR) collimations. Noise power spectrum, modulation transfer function, section sensitivity profile, iodine CT number accuracy in virtual monoenergetic images (VMIs), and iodine concentration accuracy were measured. Four participants were enrolled (between May 2021 and August 2021) in this prospective study and scanned using similar or lower radiation doses as their respective clinical examinations performed on the same day using energy-integrating detector (EID) CT. Image quality and findings from the participants’ PCD CT and EID CT examinations were compared. Results All standard technical…

Radiomic analysis offers a powerful tool for the extraction of clinically relevant information from radiologic imaging. Radiomics can be used to predict patient outcome through automated high-throughput feature extraction, using large training cohorts to elucidate subtle relationships between image characteristics and disease status. However powerful, the data-driven nature of radiomics inherently offers no insight into the biological underpinnings of the observed relationships. Early radiomics work was dominated by analysis of semantic, radiologist-defined features and carried qualitative real-world meaning. Following the rapid developments and popularity of machine learning approaches, the field moved quickly toward high-throughput agnostic analyses, resulting in increasingly large feature sets. This trend took the focus toward an increase in predictive power and further away from a biological understanding of the findings. Such a disconnect between predictor model and biological meaning will inherently limit broad clinical translation. Efforts to reintroduce biological meaning…

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…

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…

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 (n = 480), with and without AI assistance, with a 1-month minimum washout period.…

Susceptibility-weighted imaging (SWI) evolved from simple two-dimensional T2*-weighted sequences to three-dimensional sequences with improved spatial resolution and enhanced susceptibility contrast. SWI is an MRI sequence sensitive to compounds that distort the local magnetic field (eg, calcium and iron), in which the phase information can differentiate. But the term SWI is colloquially used to denote high-spatial-resolution susceptibility-enhanced sequences across different MRI vendors and sequences even when phase information is not used. The imaging appearance of SWI and related sequences strongly depends on the acquisition technique. Initially, SWI and related sequences were mostly used to improve the depiction of findings already known from standard two-dimensional T2*-weighted neuroimaging: more microbleeds in patients who are aging or with dementia or mild brain trauma; increased conspicuity of superficial siderosis in Alzheimer disease and amyloid angiopathy; and iron deposition in neurodegenerative diseases or abnormal vascular structures, such as capillary telangiectasia.…

The acute course of COVID-19 is variable and ranges from asymptomatic infection to fulminant respiratory failure. Patients recovering from COVID-19 can have persistent symptoms and CT abnormalities of variable severity. At 3 months after acute infection, a subset of patients will have CT abnormalities that include ground-glass opacity (GGO) and subpleural bands with concomitant pulmonary function abnormalities. At 6 months after acute infection, some patients have persistent CT changes to include the resolution of GGOs seen in the early recovery phase and the persistence or development of changes suggestive of fibrosis, such as reticulation with or without parenchymal distortion. The etiology of lung disease after COVID-19 may be a sequela of prolonged mechanical ventilation, COVID-19-induced acute respiratory distress syndrome (ARDS), or direct injury from the virus. Predictors of lung disease after COVID-19 include need for intensive care unit admission, mechanical ventilation, higher inflammatory markers, longer hospital stay, and a diagnosis of ARDS. Treatments of lung disease…

Background Assessment of lumbar spinal stenosis at MRI is repetitive and time consuming. Deep learning (DL) could improve ­productivity and the consistency of reporting. Purpose To develop a DL model for automated detection and classification of lumbar central canal, lateral recess, and neural ­foraminal stenosis. Materials and Methods In this retrospective study, lumbar spine MRI scans obtained from September 2015 to September 2018 were included. Studies of patients with spinal instrumentation or studies with suboptimal image quality, as well as postgadolinium studies and studies of patients with scoliosis, were excluded. Axial T2-weighted and sagittal T1-weighted images were used. Studies were split into an internal training set (80%), validation set (9%), and test set (11%). Training data were labeled by four radiologists using predefined gradings (normal, mild, moderate, and severe). A two-component DL model was developed. First, a convolutional neural network (CNN) was trained to detect the region of interest (ROI), with a second CNN for classification. An internal test set was…

Background Choroid plexuses (CPs) have been suggested as a key gateway for inflammation in experimental autoimmune encephalitis, but in vivo evidence of their involvement in multiple sclerosis (MS) is lacking. Purpose To assess CP volumetric and inflammatory changes in patients with MS versus healthy control participants. Materials and Methods This was a secondary analysis of 97 patients (61 with relapsing-remitting MS [RRMS] and 36 with progressive MS) and 44 healthy control participants who participated in three prospective 3.0-T brain MRI studies between May 2009 and September 2017. A subgroup of 37 patients and 19 healthy control participants also underwent translocator protein fluorine 18 (18F)–DPA-714 PET for neuroinflammation. Relapses and disability scores were collected at baseline and over 2 years. CPs were manually segmented on three-dimensional T1-weighted images; other brain volumes were additionally segmented. Volumes were expressed as a ratio of intracranial volume. The 18F-DPA-714 distribution volume ratio was quantified in parenchymal regions, whereas standardized…

There is currently no consensus regarding preferred clinical outcome measures following image-guided tumor ablation or clear definitions of oncologic end points. This consensus document proposes standardized definitions for a broad range of oncologic outcome measures with recommendations on how to uniformly document, analyze, and report outcomes. The initiative was coordinated by the Society of Interventional Oncology in collaboration with the Definition for the Assessment of Time-to-Event End Points in Cancer Trials, or DATECAN, group. According to predefined criteria, based on experience with clinical trials, an international panel of 62 experts convened. Recommendations were developed using the validated three-step modified Delphi consensus method. Consensus was reached on when to assess outcomes per patient, per session, or per tumor; on starting and ending time and survival time definitions; and on time-to-event end points. Although no consensus was reached on the preferred classification system to report complications, quality of life, and health economics issues, the panel…

Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial for optimizing management in lung cancer screening. Purpose To develop and validate a deep learning (DL) algorithm for malignancy risk estimation of pulmonary nodules detected at screening CT. Materials and Methods In this retrospective study, the DL algorithm was developed with 16 077 nodules (1249 malignant) collected ­between 2002 and 2004 from the National Lung Screening Trial. External validation was performed in the following three ­cohorts ­collected between 2004 and 2010 from the Danish Lung Cancer Screening Trial: a full cohort containing all 883 nodules (65 ­malignant) and two cancer-enriched cohorts with size matching (175 nodules, 59 malignant) and without size matching (177 ­nodules, 59 malignant) of benign nodules selected at random. Algorithm performance was measured by using the area under the receiver operating characteristic curve (AUC) and compared with that of the Pan-Canadian Early Detection of Lung Cancer (PanCan) model in the full cohort and a group of 11…

Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-negative assessments. Purpose To evaluate if using an artificial intelligence (AI) system could reduce workload without reducing cancer detection in breast cancer screening with digital mammography (DM) or digital breast tomosynthesis (DBT). Materials and Methods Consecutive screening-paired and independently read DM and DBT images acquired from January 2015 to December 2016 were retrospectively collected from the Córdoba Tomosynthesis Screening Trial. The original reading settings were single or double reading of DM or DBT images. An AI system computed a cancer risk score for DM and DBT examinations independently. Each original setting was compared with a simulated autonomous AI triaging strategy (the least suspicious examinations for AI are not human-read; the rest are read in the same setting as the original, and examinations not recalled by radiologists but graded as very suspicious by AI are recalled) in terms of workload,…

Background The interpretation of radiographs suffers from an ever-increasing workload in emergency and radiology departments, while missed fractures represent up to 80% of diagnostic errors in the emergency department. Purpose To assess the performance of an artificial intelligence (AI) system designed to aid radiologists and emergency physicians in the detection and localization of appendicular skeletal fractures. Materials and Methods The AI system was previously trained on 60 170 radiographs obtained in patients with trauma. The radiographs were randomly split into 70% training, 10% validation, and 20% test sets. Between 2016 and 2018, 600 adult patients in whom multiview radiographs had been obtained after a recent trauma, with or without one or more fractures of shoulder, arm, hand, pelvis, leg, and foot, were retrospectively included from 17 French medical centers. Radiographs with quality precluding human interpretation or containing only obvious fractures were excluded. Six radiologists and six emergency physicians were asked to detect and localize fractures with (n = 300)…

Background Data on the long-term pulmonary sequelae in COVID-19 are lacking. Purpose To assess symptoms, functional impairment, and residual pulmonary abnormalities on serial chest CT scans in COVID-19 survivors discharged from hospital at up to 1-year follow-up. Materials and Methods Adult patients with COVID-19 discharged between March 2020 and June 2020 were prospectively evaluated at 3 months and 1 year through systematic assessment of symptoms, functional impairment, and thoracic CT scans as part of the PHENOTYPE study, an observational cohort study in COVID-19 survivors. Lung function testing was limited to participants with CT abnormalities and/or persistent breathlessness. Bonferroni correction was used. Results Eighty participants (mean age, 59 years ± 13 [SD]; 53 men) were assessed. At outpatient review, persistent breathlessness was reported in 37 of the 80 participants (46%) and cough was reported in 17 (21%). CT scans in 73 participants after discharge (median, 105 days; IQR, 95-141 days) revealed persistent abnormalities in 41 participants (56%), with ground-glass…

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…

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…

Background Macrotrabecular-massive (MTM) subtype and vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. Purpose To estimate the potential of preoperative CT in the prediction of MTM subtype and VETC pattern. Materials and Methods Patients who underwent surgical resection or liver transplant and preoperative CT for HCC between January 2015 and June 2018 were retrospectively included in the primary cohort. CT imaging features were evaluated by two radiologists. Predictors associated with the MTM subtype or VETC pattern were determined by using logistic regression analyses and the performance was tested in a validation cohort. Prognostic factors associated with early recurrence after surgical resection were identified by using Cox regression analyses. Results The primary cohort included 170 patients (median age, 55 years; interquartile range, 48–63 years; 152 men). Serum α-fetoprotein level higher than 100 ng/mL (odds ratio [OR], 4.3; 95% CI: 2.1, 9.2; P < .001), intratumor necrosis (OR, 5.2; 95% CI: 2.5,…

Five cases of axillary lymphadenopathy are presented, which occurred after COVID-19 vaccination and mimicked metastasis in a vulnerable oncologic patient group. Initial radiologic diagnosis raised concerns for metastasis. However, further investigation revealed that patients received COVID-19 vaccinations in the ipsilateral arm prior to imaging. In two cases, lymph node biopsy results confirmed vaccination-related reactive lymphadenopathy. Ipsilateral axillary swelling or lymphadenopathy was reported based on symptoms and physical examination in COVID-19 vaccine trials. Knowledge of the potential for COVID-19 vaccine-related ipsilateral adenopathy is necessary to avoid unnecessary biopsy and change in therapy. © RSNA, 2021.

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.…

Background Previously, the risk of death from breast cancer was analyzed for women participating versus those not participating in the last screening examination before breast cancer diagnosis. Consecutive attendance patterns may further refine estimates. Purpose To estimate the effect of participation in successive mammographic screening examinations on breast cancer mortality. Materials and Methods Participation data for Swedish women eligible for screening mammography in nine counties from 1992 to 2016 were linked with data from registries and regional cancer centers for breast cancer diagnosis, cause, and date of death (Uppsala University ethics committee registration number: 2017/147). Incidence-based breast cancer mortality was calculated by whether the women had participated in the most recent screening examination prior to diagnosis only (intermittent participants), the penultimate screening examination only (lapsed participants), both examinations (serial participants), or neither examination (serial nonparticipants). Rates were analyzed with Poisson regression. We also…

Background The biologic meaning of prognostic radiomics phenotypes remains poorly understood, hampered in part by lack of multicenter reproducible evidence. Purpose To uncover the biologic meaning of individual prognostic radiomics phenotypes in glioblastomas using paired MRI and RNA sequencing data and to validate the reproducibility of the identified radiogenomics linkages externally. Materials and Methods This retrospective multicenter study included four data sets gathered between January 2015 and December 2016. From a radiomics analysis set, a 13-feature radiomics signature was built using preoperative MRI for overall survival prediction. Using a radiogenomics training set with both MRI and RNA sequencing, biologic pathways were enriched and correlated with each of the 13 radiomics phenotypes. Radiomics-correlated key genes were identified to derive a prognostic radiomics gene expression (RadGene) score. The reproducibility of identified pathways and genes was validated with an external test set and a public data set (The Cancer Genome Atlas [TCGA]). A log-rank test was…

Infection with SARS-CoV-2 ranges from an asymptomatic condition to a severe and sometimes fatal disease, with mortality most frequently being the result of acute lung injury. The role of imaging has evolved during the pandemic, with CT initially being an alternative and possibly superior testing method compared with reverse transcriptase-polymerase chain reaction (RT-PCR) testing and evolving to having a more limited role based on specific indications. Several classification and reporting schemes were developed for chest imaging early during the pandemic for patients suspected of having COVID-19 to aid in triage when the availability of RT-PCR testing was limited and its level of performance was 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 radiographs and CT images showed correlations with critical illness and a need for mechanical ventilation. In addition to pulmonary manifestations,…

Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreader variability. Purpose To investigate whether a proposed content-based image retrieval (CBIR) of similar chest CT images by using deep learning can aid in the diagnosis of ILD by readers with different levels of experience. Materials and Methods This retrospective study included patients with confirmed ILD after multidisciplinary discussion and available CT images identified between January 2000 and December 2015. Database was composed of four disease classes: usual interstitial pneumonia (UIP), nonspecific interstitial pneumonia (NSIP), cryptogenic organizing pneumonia, and chronic hypersensitivity pneumonitis. Eighty patients were selected as queries from the database. The proposed CBIR retrieved the top three similar CT images with diagnosis from the database by comparing the extent and distribution of different regional disease patterns quantified by a deep learning algorithm. Eight readers with varying experience interpreted the…

The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19-positive…

Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and classification of primary bone tumors on radiographs. Materials and Methods This retrospective study analyzed bone tumors on radiographs acquired prior to treatment and obtained from patient data from January 2000 to June 2020. Benign or malignant bone tumors were diagnosed in all patients by using the histopathologic findings as the reference standard. By using split-sample validation, 70% of the patients were assigned to the training set, 15% were assigned to the validation set, and 15% were assigned to the test set. The final performance was evaluated on an external test set by using geographic validation, with accuracy, sensitivity, specificity, and 95% CIs being used for classification, the intersection over union (IoU) being used for bounding box placements, and the Dice score being used for segmentations. Results Radiographs from 934…

Vaccination-associated adenopathy is a frequent imaging finding after administration of COVID-19 vaccines that may lead to a diagnostic conundrum in patients with manifest or suspected cancer, in whom it may be indistinguishable from malignant nodal involvement. To help the medical community address this concern in the absence of studies and evidence-based guidelines, this special report offers recommendations developed by a multidisciplinary panel of experts from three of the leading tertiary care cancer centers in the United States. According to these recommendations, some routine imaging examinations, such as those for screening, should be scheduled before or at least 6 weeks after the final vaccination dose to allow for any reactive adenopathy to resolve. However, there should be no delay of other clinically indicated imaging (eg, for acute symptoms, short-interval treatment monitoring, urgent treatment planning or complications) due to prior vaccination. The vaccine should be administered on the side contralateral to the primary or suspected cancer, and both doses should be…

Background The long-term post-acute pulmonary sequelae of COVID-19 remain unknown. Purpose To evaluate lung injury in patients affected by COVID-19 pneumonia at the 6-month follow-up CT examination compared with the baseline chest CT examination. Materials and Methods From March 19, 2020, to May 24, 2020, patients with moderate to severe COVID-19 pneumonia who had undergone baseline chest CT were prospectively enrolled at their 6-month follow-up. The CT qualitative findings, semiquantitative Lung Severity Score (LSS), and the well-aerated lung volume at quantitative chest CT (QCCT) analysis were analyzed. The performance of the baseline LSS and QCCT findings for predicting fibrosis-like changes (reticular pattern and/or honeycombing) at the 6-month follow-up chest CT examination was tested by using receiver operating characteristic curves. Univariable and multivariable logistic regression analyses were used to test clinical and radiologic features that were predictive of fibrosis-like changes. The multivariable analysis was performed with clinical parameters alone (clinical model),…

Background Missing MRI sequences represent an obstacle in the development and use of deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing brain MRI scans using generative adversarial networks (GANs) allows for the use of a DL model for brain lesion segmentation that requires T1-weighted images, postcontrast T1-weighted images, fluid-attenuated inversion recovery (FLAIR) images, and T2-weighted images. Materials and Methods In this retrospective study, brain MRI scans obtained between 2011 and 2019 were collected, and scenarios were simulated in which the T1-weighted images and FLAIR images were missing. Two GANs were trained, validated, and tested using 210 glioblastomas (GBMs) (Multimodal Brain Tumor Image Segmentation Benchmark [BRATS] 2017) to generate T1-weighted images from postcontrast T1-weighted images and FLAIR images from T2-weighted images. The quality of the generated images was evaluated with mean squared error (MSE) and the structural similarity index (SSI). The segmentations obtained with the generated scans were compared with…

Use of molecular targeting agents and immune checkpoint inhibitors (ICIs) has increased the frequency and broadened the spectrum of lung toxicity, particularly in patients with cancer. The diagnosis of drug-related pneumonitis (DRP) is usually achieved by excluding other potential known causes. Awareness of the incidence and risk factors for DRP is becoming increasingly important. The severity of symptoms associated with DRP may range from mild or none to life-threatening with rapid progression to death. Imaging features of DRP should be assessed in consideration of the distribution of lung parenchymal abnormalities (radiologic pattern approach). The CT patterns reflect acute (diffuse alveolar damage) interstitial pneumonia and transient (simple pulmonary eosinophilia) lung abnormality, subacute interstitial disease (organizing pneumonia and hypersensitivity pneumonitis), and chronic interstitial disease (nonspecific interstitial pneumonia). A single drug can be associated with multiple radiologic patterns. Treatment of a patient suspected of having DRP generally consists of drug…

Background SARS-CoV-2 targets angiotensin-converting enzyme 2–expressing cells in the respiratory tract. There are reports of breathlessness in patients many months after infection. Purpose To determine whether hyperpolarized xenon 129 MRI (XeMRI) imaging could be used to identify the possible cause of breathlessness in patients at 3 months after hospital discharge following COVID-19 infection. Materials and Methods This prospective study was undertaken between August and December of 2020, with patients and healthy control volunteers being enrolled. All patients underwent lung function tests; ventilation and dissolved-phase XeMRI, with the mean red blood cell (RBC) to tissue or plasma (TP) ratio being calculated; and a low-dose chest CT, with scans being scored for the degree of abnormalities after COVID-19. Healthy control volunteers underwent XeMRI. The intraclass correlation coefficient was calculated for volunteer and patient scans to assess repeatability. A Wilcoxon rank sum test and Cohen effect size calculation were performed to assess differences in the RBC/TP ratio between…

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…

Background Advances in computer processing and improvements in data availability have led to the development of machine learning (ML) techniques for mammographic imaging. Purpose To evaluate the reported performance of stand-alone ML applications for screening mammography workflow. Materials and Methods Ovid Embase, Ovid Medline, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science literature databases were searched for relevant studies published from January 2012 to September 2020. The study was registered with the PROSPERO International Prospective Register of Systematic Reviews (protocol no. CRD42019156016). Stand-alone technology was defined as a ML algorithm that can be used independently of a human reader. Studies were quality assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and the Prediction Model Risk of Bias Assessment Tool, and reporting was evaluated using the Checklist for Artificial Intelligence in Medical Imaging. A primary meta-analysis included the top-performing algorithm and corresponding reader performance from which…

Normal physiologic function of organs requires a circulation of interstitial fluid to deliver nutrients and clear cellular waste products. Lymphatic vessels serve as collectors of this fluid in most organs; however, these vessels are absent in the central nervous system. How the central nervous system maintains tight control of extracellular conditions has been a fundamental question in neuroscience until recent discovery of the glial-lymphatic, or glymphatic, system was made this past decade. Networks of paravascular channels surrounding pial and parenchymal arteries and veins were found that extend into the walls of capillaries to allow fluid transport and exchange between the interstitial and cerebrospinal fluid spaces. The currently understood anatomy and physiology of the glymphatic system is reviewed, with the paravascular space presented as an intrinsic component of healthy pial and parenchymal cerebral blood vessels. Glymphatic system behavior in animal models of health and disease, and its enhanced function during sleep, are discussed. The evolving understanding of…

Background The chest CT manifestations of COVID-19 from hospitalization to convalescence after 1 year are unknown. Purpose To assess chest CT manifestations of COVID-19 up to 1 year after symptom onset. Materials and Methods Patients were enrolled if they were admitted to the hospital because of COVID-19 and underwent CT during hospitalization at two isolation centers between January 27, 2020, and March 31, 2020. In a prospective study, three serial chest CT scans were obtained at approximately 3, 7, and 12 months after symptom onset and were longitudinally analyzed. The total CT score of pulmonary lobe involvement, ranging from 0 to 25, was assessed (score of 1–5 for each lobe). Univariable and multivariable logistic regression analyses were performed to explore independent risk factors for residual CT abnormalities after 1 year. Results A total of 209 study participants (mean age, 49 years ± 13 [standard deviation]; 116 women) were evaluated. CT abnormalities had resolved in 61% of participants (128 of 209) at 3 months and in 75% of participants (156 of 209) at 12 months. Among…

It may seem unlikely that the field of radiology perpetuates disparities in health care, as most radiologists never interact directly with patients, and racial bias is not an obvious factor when interpreting images. However, a closer look reveals that imaging plays an important role in the propagation of disparities. For example, many advanced and resource-intensive imaging modalities, such as MRI and PET/CT, are generally less available in the hospitals frequented by people of color, and when they are available, access is impeded due to longer travel and wait times. Furthermore, their images may be of lower quality, and their interpretations may be more error prone. The aggregate effect of these imaging acquisition and interpretation disparities in conjunction with social factors is insufficiently recognized as part of the wide variation in disease outcomes seen between races in America. Understanding the nature of disparities in radiology is important to effectively deploy the resources and expertise necessary to mitigate disparities through diversity and inclusion efforts,…

The glymphatic system is a recently discovered network unique to the central nervous system that allows for dynamic exchange of interstitial fluid (ISF) and cerebrospinal fluid (CSF). As detailed in part I, ISF and CSF transport along paravascular channels of the penetrating arteries and possibly veins allow essential clearance of neurotoxic solutes from the interstitium to the CSF efflux pathways. Imaging tests to investigate this neurophysiologic function, although challenging, are being developed and are reviewed herein. These include direct visualization of CSF transport using postcontrast imaging techniques following intravenous or intrathecal administration of contrast material and indirect glymphatic assessment with detection of enlarged perivascular spaces. Application of MRI techniques, including intravoxel incoherent motion, diffusion tensor imaging, and chemical exchange saturation transfer, is also discussed, as are methods for imaging dural lymphatic channels involved with CSF efflux. Subsequently, glymphatic function is considered in the context of proteinopathies…

Fibrotic interstitial lung abnormalities in survivors of severe COVID-19 depicted on 6-month CT scans were persistent on 1-year CT scans and were negatively correlated with the lung diffusion capacity.

Background Dynamic contrast-enhanced (DCE) photoacoustic (PA) imaging (PAI) is a novel noninvasive imaging modality that uses the differences in optical absorption of oxyhemoglobin and deoxyhemoglobin and may be performed in a dynamic fashion to image the indocyanine green (ICG) pharmacokinetics in the liver. Purpose To determine whether DCE PAI parameters (maximum peak time [Tmax] and half-life [T1/2]) derived from the PA liver function curve correlate with fibrosis determined using histopathologic analysis. Materials and Methods Between June 2020 and October 2020, 28 male mice aged 8 weeks were intraperitoneally injected with carbon tetrachloride solution every 2 days to establish a liver fibrosis model. At the 1st, 4th, and 8th week of modeling, the changes in liver structure were monitored dynamically by using a PA technique. The Tmax and T1/2 of ICG were calculated at different pathologic stages and within a control group. Corresponding liver histopathologic results and blood biochemical data were obtained. Spearman rank correlation was used to evaluate the relationship between…

Background Macrophage burden is a major factor in the risk of atherosclerotic plaque rupture, and its evaluation remains challenging with molecular noninvasive imaging approaches. Photon-counting CT (PCCT) with k-edge imaging aims to allow for the specific detection of macrophages using gold nanoparticles. Purpose To perform k-edge imaging in combination with gold nanoparticles to detect and quantify the macrophage burden within the atherosclerotic aortas of rabbits. Materials and Methods Atherosclerotic and control New Zealand white rabbits were imaged before and at several time points up to 2 days after intravenous injection of gold nanoparticles (3.5 mL/kg, 65 mg gold per milliliter). Aortic CT angiography was performed at the end of the follow-up using an intravenous injection of an iodinated contrast material. Gold k-edge and conventional CT images were reconstructed for qualitative and quantitative assessment of the macrophage burden. PCCT imaging results were compared with findings at histologic examination, quantitative histomorphometry, transmission electron microscopy, and…

Background Opening of the blood-brain barrier (BBB) induced with MRI-guided focused ultrasound has been shown in experimental animal models to reduce amyloid-β plaque burden, improve memory performance, and facilitate delivery of therapeutic agents to the brain. However, physiologic effects of this procedure in humans with Alzheimer disease (AD) require further investigation. Purpose To assess imaging effects of focused ultrasound–induced BBB opening in the hippocampus of human participants with early AD and to evaluate fluid flow patterns after BBB opening by using serial contrast-enhanced MRI. Materials and Methods Study participants with early AD recruited to a Health Insurance Portability and Accountability Act–compliant, prospective, ongoing phase II clinical trial (ClinicalTrials.gov identifier, NCT03671889) underwent three separate focused ultrasound–induced BBB opening procedures that used a 220-kHz transducer with a concomitant intravenous microbubble contrast agent administered at 2-week intervals targeting the hippocampus and entorhinal cortex between October 2018 and May…

Background Microwave ablation (MWA) and radiofrequency ablation (RFA) have recently attracted interest as minimally invasive treatment modalities for papillary thyroid carcinoma (PTC). However, the ablation outcomes of T1N0M0 PTC are not well characterized. Purpose To evaluate the efficacy and safety of thermal ablation (MWA or RFA) of solitary T1N0M0 PTC in patients who were ineligible for (due to presence of comorbid cardiovascular disease, renal failure, other malignancy, etc) or who refused surgery. Materials and Methods This was a retrospective multicenter study of 847 patients (660 women) who underwent thermal ablation for PTC (673 T1a, 174 T1b) between March 2015 and March 2020; of these patients, 645 underwent MWA and 202 underwent RFA. The mean age of patients was 46 years ± 11 (standard deviation) (age range, 18–81 years); the mean follow-up time was 22 months ± 13 (range, 6–60 months). Changes in tumor size and volume and the rates of technical success, tumor disappearance, disease progression, and complications were assessed. Results The technical success rate was 100%.…

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…

Background Diagnostic reference levels (DRLs) and achievable doses (ADs) were developed for the 10 most commonly performed pediatric CT examinations in the United States using the American College of Radiology Dose Index Registry. Purpose To develop robust, current, national DRLs and ADs for the 10 most commonly performed pediatric CT examinations as a function of patient age and size. Materials and Methods Data on 10 pediatric (ie, patients aged 18 years and younger) CT examinations performed between 2016 and 2020 at 1625 facilities were analyzed. For head and neck examinations, dose indexes were analyzed based on patient age; for body examinations, dose indexes were analyzed for patient age and effective diameter. Data from 1 543 535 examinations provided medians for AD and 75th percentiles for DRLs for volume CT dose index (CTDIvol), dose-length product (DLP), and size-specific dose estimate (SSDE). Results Of all facilities analyzed, 66% of the facilities (1068 of 1625) were community hospitals, 16% (264 of 1625) were freestanding centers, 9.5% (154 of 1625) were academic…

Background Evaluation of the glymphatic system with intrathecal contrast material injection has limited clinical use. Purpose To investigate the feasibility of using serial intravenous contrast-enhanced T1 mapping in the quantitative evaluation of putative dynamic glymphatic activity in various brain regions and to demonstrate the effect of sleep on glymphatic activity in humans. Materials and Methods In this prospective study from May 2019 to February 2020, 25 healthy participants (mean age, 25 years ± 2 [standard deviation]; 15 men) underwent two cycles of MRI (day and night cycles). For each cycle, T1 maps were acquired at baseline and 0.5, 1, 1.5, 2, and 12 hours after intravenous contrast material injection. For the night cycle, participants had a normal night of sleep between 2 and 12 hours. The time (tmin) to reach the minimum T1 value (T1min), the absolute difference between baseline T1 and T1min (peak ΔT1), and the slope between two measurements at 2 and 12 hours (slope[2h-12h]) were determined from T1 value–time curves in cerebral gray matter (GM), cerebral white matter…

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment…

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage I non–small cell lung cancer (NSCLC). Purpose To develop a deep learning signature for N2 metastasis prediction and prognosis stratification in clinical stage I NSCLC. Materials and Methods In this retrospective study conducted from May 2020 to October 2020 in a population with clinical stage I NSCLC, an internal cohort was adopted to establish a deep learning signature. Subsequently, the predictive efficacy and biologic basis of the proposed signature were investigated in an external cohort. A multicenter diagnostic trial (registration number: ChiCTR2000041310) was also performed to evaluate its clinical utility. Finally, on the basis of the N2 risk scores, the instructive significance of the signature in prognostic stratification was explored. The diagnostic efficiency was quantified with the area under the receiver operating characteristic curve (AUC), and the survival outcomes were assessed using the Cox proportional hazards model. Results A total of 3096 patients (mean age ±…

Background Ischemic lesion net water uptake (NWU) at noncontrast head CT enables quantification of cerebral edema in patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO). Purpose To assess whether favorable venous outflow (VO) profiles at CT angiography are associated with reduced NWU and good functional outcomes in patients with AIS due to LVO. Materials and Methods This multicenter retrospective cohort study evaluated consecutive patients with AIS due to LVO who underwent thrombectomy triage between January 2013 and December 2019. Arterial collateral vessel status (Tan scale) and venous output were measured at CT angiography. Venous outflow was graded with use of the cortical vein opacification score, which quantifies opacification of the vein of Labbé, sphenoparietal sinus, and superficial middle cerebral vein. Favorable VO was regarded as a score of 3–6 and unfavorable VO as a score of 0–2. NWU was determined at follow-up noncontrast CT. Multivariable regression analyses were performed to determine the association between favorable VO profiles and NWU…