Publications

BACKGROUND: Body composition is associated with mortality; however its routine assessment is too time-consuming.

PURPOSE: To demonstrate the value of artificial intelligence (AI) to extract body composition measures from routine studies, we aimed to develop a fully automated AI approach to measure fat and muscles masses, to validate its clinical discriminatory value, and to provide the code, training data and workflow solutions to facilitate its integration into local practice.

METHODS: We developed a neural network that quantified the tissue components at the L3 vertebral body level using data from the Liver Tumor Challenge (LiTS) and a pancreatic cancer cohort. We classified sarcopenia using accepted skeletal muscle index cut-offs and visceral fat based its median value. We used Kaplan Meier curves and Cox regression analysis to assess the association between these measures and mortality.

RESULTS: Applying the algorithm trained on LiTS data to the local cohort yielded good agreement [>0.8 intraclass correlation (ICC)]; when trained on both datasets, it had excellent agreement (>0.9 ICC). The pancreatic cancer cohort had 136 patients (mean age: 67 ± 11 years; 54% women); 15% had sarcopenia; mean visceral fat was 142 cm2. Concurrent with prior research, we found a significant association between sarcopenia and mortality [mean survival of 15 ± 12 vs. 22 ± 12 (p < 0.05), adjusted HR of 1.58 (95% CI: 1.03-3.33)] but no association between visceral fat and mortality. The detector analysis took 1 ± 0.5 s.

CONCLUSIONS: AI body composition analysis can provide meaningful imaging biomarkers from routine exams demonstrating AI's ability to further enhance the clinical value of radiology reports.

Primary liver cancer is the fourth leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) comprising the vast majority of primary liver malignancies. Imaging plays a central role in HCC diagnosis and management. As a result, the content and structure of radiology reports are of utmost importance in guiding clinical management. The Liver Imaging Reporting and Data System (LI-RADS) provides guidance for standardized reporting of liver observations in patients who are at risk for HCC. LI-RADS standardized reporting intends to inform patient treatment and facilitate multidisciplinary communication and decisions, taking into consideration individual clinical factors. Depending on the context, observations may be reported individually, in aggregate, or as a combination of both. LI-RADS provides two templates for reporting liver observations: in a single continuous paragraph or in a structured format with keywords and imaging findings. The authors clarify terminology that is pertinent to reporting, highlight the benefits of structured reports, discuss the applicability of LI-RADS for liver CT and MRI, review the elements of a standardized LI-RADS report, provide guidance on the description of LI-RADS observations exemplified with two case-based reporting templates, illustrate relevant imaging findings and components to be included when reporting specific clinical scenarios, and discuss future directions. An invited commentary by Yano is available online. Online supplemental material is available for this article. Work of the U.S. Government published under an exclusive license with the RSNA.

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the lexicon, technique, interpretation, reporting, and data collection of liver imaging. Developed specifically for assessment of liver observations in patients at risk for hepatocellular carcinoma (HCC), LI-RADS classifies hepatic observations on the basis of the probability of their being HCC, from LR-1 (definitely benign) to LR-5 (definitely HCC). This article discusses the technical requirements, major features, and ancillary features of and a systematic approach for using the LI-RADS diagnostic algorithm, with special emphasis on MR imaging.

Many survivors from severe coronavirus disease 2019 (COVID-19) suffer from persistent dyspnea and fatigue long after resolution of the active infection. In a cohort of 21 consecutive severe post-COVID-19 survivors admitted to an inpatient rehabilitation hospital, 16 (76%) of them had at least one sonographic abnormality of diaphragm muscle structure or function. This corresponded to a significant reduction in diaphragm muscle contractility as represented by thickening ratio (muscle thickness at maximal inspiration/end-expiration) for the post-COVID-19 compared to non-COVID-19 cohorts. These findings may shed new light on neuromuscular respiratory dysfunction as a contributor to prolonged functional impairments after hospitalization for post-COVID-19.

Acute and chronic kidney failure is common in hospitalized patients with COVID-19, yet the mechanism of injury and predisposing factors remain poorly understood. We investigated the role of complement activation by determining the levels of deposited complement components (C1q, C3, FH, C5b-9) and immunoglobulin along with the expression levels of the injury-associated molecules spleen tyrosine kinase (Syk), mucin-1 (MUC1) and calcium/calmodulin-dependent protein kinase IV (CaMK4) in the kidney tissues of people who succumbed to COVID-19. We report increased deposition of C1q, C3, C5b-9, total immunoglobulin, and high expression levels of Syk, MUC1 and CaMK4 in the kidneys of COVID-19 patients. Our study provides strong rationale for the expansion of trials involving the use of inhibitors of these molecules, in particular C1q, C3, Syk, MUC1 and CaMK4 to treat patients with COVID-19.

RATIONALE AND OBJECTIVES: Radiology participation is necessary in oncology multidisciplinary conferences (MDCs), but the resources required to do so are often unaccounted for. In this prospective study we provide an analysis of resource utilization as a function of outcomes for all MDCs covered by an entire radiology section and provide a time-based cost estimate.

MATERIALS AND METHODS: Following institutional review board approval, prospective data on all MDCs covered by abdominal radiologists at a single tertiary care academic center were obtained over nine weeks. A predefined questionnaire was used by a single observer who attended every imaging review and recorded the total time spent by the radiologists and several outcome measures. The total time recorded was used to provide a time-based cost estimate using a national salary survey.

RESULTS: Six radiologists participated in a total of 57 MDCs, with 577 cases reviewed and discussed. 181 (31%) cases were performed at outside facilities requiring full reinterpretation. Clinically significant revisions to original reports were recorded in 107 (18.5%) cases. Radiologist input directly resulted in alteration of cancer staging in 65 (11%) patients and specific recommendations for follow-up diagnostic workup in 280 (48%) of cases. The mean total time devoted by the staff radiologist per week to MDCs was 18.7 hours/week, nearly a half of full-time effort, or 8% of total effort per radiologist. The total annual projected cost of radiology coverage for each weekly MDC was $26,920.

CONCLUSION: Section-wide radiologist participation in MDCs directly resulted in change in clinical management in nearly half of reviewed cases. This was achieved at a notable time cost, highlighting the need for efficient integration of radiology MDC participation into radiologist workflow and compensation models.

Infections of the cardiovascular system may present with nonspecific symptoms, and it is common for patients to undergo multiple investigations to arrive at the diagnosis. Echocardiography is central to the diagnosis of endocarditis and pericarditis. However, cardiac computed tomography (CT) and magnetic resonance imaging also play an additive role in these diagnoses; in fact, magnetic resonance imaging is central to the diagnosis of myocarditis. Functional imaging (fluorine-18 fluorodeoxyglucose-positron emission tomography/CT and radiolabeled white blood cell single-photon emission computed tomography/CT) is useful in the diagnosis in prosthesis-related and disseminated infection. This pictorial review will detail the most commonly encountered cardiovascular bacterial and viral infections, including coronavirus disease-2019, in clinical practice and provide an evidence basis for the selection of each imaging modality in the investigation of native tissues and common prostheses.

HCC incidence continues to increase worldwide and is most frequently discovered at an advanced stage when limited curative options are available. Combination locoregional therapies have emerged to improve patient survival and quality of life or downstage patients to curative options. The increasing options for locoregional therapy combinations require an understanding of the expected post-treatment imaging appearance in order to assess treatment response. This review aims to describe the synergy between TACE combined with thermal ablation and TACE combined with SBRT. We will also illustrate expected imaging findings that determine treatment efficacy based on the mechanism of tissue injury using the LI-RADS Treatment Response Algorithm.

Contrast-enhanced MR imaging plays an important role in the evaluation of patients with chronic liver disease, particularly for detection and characterization of liver lesions. The two most commonly used contrast agents for liver MR imaging are extracellular agents (ECAs) and hepatobiliary agents (HBAs). In patients with liver disease, the main advantage of ECA-enhanced MR imaging is its high specificity for the diagnosis of progressed HCCs. Conversely, HBAs have an additional contrast mechanism, which results in high liver-to-lesion contrast and highest sensitivity for lesion detection in the hepatobiliary phase. Emerging data suggest that features depicted on contrast-enhanced MR imaging scans are related to tumor biology and are predictive of patients' prognosis, likely to further expand the role of contrast-enhanced MR imaging in the clinical care of patients with chronic liver disease.

In many tumors, cancer cells take up large quantities of glucose and metabolize it into lactate, even in the presence of sufficient oxygen to support oxidative metabolism. It has been hypothesized that this malignant metabolic phenotype supports cancer growth and metastasis, and that reversal of this so-called "Warburg effect" may selectively harm cancer cells. Conversion of glucose to lactate can be reduced by ablation or inhibition of lactate dehydrogenase (LDH), the enzyme responsible for conversion of pyruvate to lactate at the endpoint of glycolysis. Recently developed inhibitors of LDH provide new opportunities to investigate the role of this metabolic pathway in cancer. Here we show that magnetic resonance spectroscopic imaging of hyperpolarized pyruvate and its metabolites in models of breast and lung cancer reveal that inhibition of LDH was readily visualized through reduction in label exchange between pyruvate and lactate, while genetic ablation of the LDH-A isoform alone had smaller effects. During the acute phase of LDH inhibition in breast cancer, no discernible bicarbonate signal was observed and small signals from alanine were unchanged.