Preresection Radiologic Assessment and Imaging Features of 156 Pathologically Proven Adrenal Adenomas.

PURPOSE: The aims of the study were to assess the typical and atypical radiologic features of pathologically proven adrenal adenomas and to determine the relationship between the radiologic and histopathologic classification. METHODS: We retrospectively studied 156 pathologically proven adrenal adenomas in 154 patients from our institutional databases who have computed tomography (CT) and/or magnetic resonance imaging (MRI) examinations before intervention. We determined the histopathologic diagnosis (typical or atypical) using Weiss scoring and classified the adenomas radiologically into typical, atypical, or indeterminate based on lesion size, precontrast CT attenuation, absolute percentage washout, calcification, and necrosis. The κ statistic was used to assess the agreement between radiologists. The Fisher exact test was used to compare the radiologic and pathological classifications. RESULTS: In consensus, there were 83 typical, 42 atypical, and 31 indeterminate adrenal lesions. Logistic regression model showed that radiologically atypical adenoma was significantly associated with larger size, lobulated shape, higher unenhanced CT attenuation, heterogeneous appearance, nonfunctioning status, absolute percentage washout of less than 60%, and a signal intensity index of less than 16.5%.Pathologically, 147 adenomas were pathologically typical (Weiss 0), and 9 adenomas were pathologically atypical (Weiss 1-2). Radiologically, there was substantial agreement between both readers, with Cohen κ at 0.71. Approximately 98% of radiologically typical adenomas were pathologically typical. Only 17% of radiologically atypical adenomas were pathologically atypical. All radiologically indeterminate adenomas were pathologically typical. However, some of the radiologically indeterminate and typical adenomas still had an atypical component on pathologic analysis, such as necrosis, nuclear atypia, or oncocytic features. CONCLUSIONS: Radiologically atypical lesion was significantly associated with larger size and higher unenhanced CT attenuation. Approximately 27% of the cases demonstrated atypical features on imaging. Most radiologically atypical adrenal adenomas are pathologically typical.

Calcified Adrenal Lesions: Pattern Recognition Approach on Computed Tomography With Pathologic Correlation.

Incidental adrenal lesions are found in 2% to 10% of the population. The presence and pattern of calcifications, in conjunction with other clinical and imaging features, such as soft tissue attenuation, enhancement, and laterality, can aid in narrowing a differential diagnosis, thereby preventing unnecessary biopsies and avoiding delays in management. Calcified adrenal lesions can be categorized under the clinical and laboratory headings of normal adrenal function, hyperfunctioning adrenal tissue, and adrenal insufficiency. In this review, we provide an algorithmic approach to assessing calcified adrenal nodules with correlative radiologic findings.

Automated Volumetric Assessment of Hepatocellular Carcinoma Response to Sorafenib: A Pilot Study.

PURPOSE: This pilot study evaluates the feasibility of automated volumetric quantification of hepatocellular carcinoma (HCC) as an imaging biomarker to assess treatment response for sorafenib. METHODS: In this institutional review board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study, a training database of manually labeled background liver, enhancing and nonenhancing tumor tissue was established using pretherapy and first posttherapy multiphasic computed tomography images from a registry of 13 HCC patients. For each patient, Hounsfield density and geometry-based feature images were generated from registered multiphasic computed tomography data sets and used as the input for a random forest-based classifier of enhancing and nonenhancing tumor tissue. Leave-one-out cross-validation of the dice similarity measure was applied to quantify the classifier accuracy. A Cox regression model was used to confirm volume changes as predictors of time to progression (TTP) of target lesions for both manual and automatic methods. RESULTS: When compared with manual labels, an overall classification accuracy of dice similarity coefficient of 0.71 for pretherapy and 0.66 posttherapy enhancing tumor labels and 0.45 for pretherapy and 0.59 for posttherapy nonenhancing tumor labels was observed. Automated methods for quantifying volumetric changes in the enhancing lesion agreed with manual methods and were observed as a significant predictor of TTP. CONCLUSIONS: Automated volumetric analysis was determined to be feasible for monitoring HCC response to treatment. The information extracted using automated volumetrics is likely to reproduce labor-intensive manual data and provide a good predictor for TTP. Further work will extend these studies to additional treatment modalities and larger patient populations.

Spectrum of Pitfalls, Pseudolesions, and Potential Misdiagnoses in Cirrhosis.

OBJECTIVE: The purposes of this article are to review a variety of pitfalls in liver imaging that can lead to the inaccurate diagnosis of focal hepatic lesions in cirrhosis, to describe the pathophysiologic processes of these pitfalls, and to provide specific clues for achieving the correct diagnoses. CONCLUSION: Cirrhosis complicates liver imaging. The distortion and replacement of normal liver parenchyma by fibrous and regenerative tissue can change the typical appearance of many benign lesions, causing them to be misinterpreted as malignancy. In addition, the high incidence and prevalence of hepatocellular carcinoma among patients with cirrhosis put radiologists on high alert for any suspicious findings, especially because not all hepatocellular carcinomas have a typical imaging appearance.

Spectrum of Pitfalls, Pseudolesions, and Misdiagnoses in Noncirrhotic Liver.

OBJECTIVE: The purpose of this article is to illustrate the various pitfalls, mimics, and atypical features that can lead to inaccurate diagnosis of focal lesions in a noncirrhotic liver. The content includes relevant pathogenesis and background as well as specific clues that can be used to reach an accurate diagnosis. CONCLUSION: When assessing focal hepatic lesions, it is important to avoid pitfalls and misdiagnoses that can alter the management plan. Helpful strategies for avoiding pitfalls include paying close attention to the clinical history of the patient, carefully evaluating all of the available imaging studies, and being aware of the various radiologic mimics.

Multimodality annotated hepatocellular carcinoma data set including pre- and post-TACE with imaging segmentation.

Hepatocellular carcinoma (HCC) is the most common primary liver neoplasm, and its incidence has doubled over the past two decades owing to increasing risk factors. Despite surveillance, most HCC cases are diagnosed at advanced stages and can only be treated using transarterial chemo-embolization (TACE) or systemic therapy. TACE failure may occur with incidence reaching up to 60% of cases, leaving patients with a financial and emotional burden. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from pre-procedural computed tomography (CT) studies. This data report defines the HCC-TACE data collection of confirmed HCC patients who underwent TACE and have pre- and post-procedure CT imaging studies and available treatment outcomes (time-to-progression and overall survival). Clinically curated segmentation of pre-procedural CT studies was done for the purpose of algorithm training for prediction and automatic liver tumor segmentation.

Errors and Misinterpretations in Imaging of Chronic Liver Diseases.

MRI is an important problem-solving tool for accurate characterization of liver lesions. Chronic liver disease alters the typical imaging characteristics and complicates liver imaging. Awareness of imaging pitfalls and technical artifacts and ways to mitigate them allows for more accurate and timely diagnosis.

A Concise Review of the Multimodality Imaging Features of Renal Cell Carcinoma.

The evaluation of renal cell carcinoma (RCC) is routinely performed using the multimodality imaging approach, including ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Ultrasonography is the most frequently used imaging modality for the initial diagnosis of renal masses. The modality of choice for the characterization of the renal mass is multiphasic CT. Recent advances in CT technology have led to its widespread use as a powerful tool for preoperative planning, reducing the need for catheter angiography for the evaluation of vascular invasion. CT is also the standard imaging modality for staging and follow-up. MRI serves as a problem-solving tool in selected cases of undefined renal lesions. Newer MRI techniques, such as arterial spin labeling and diffusion-weighted imaging, have the potential to characterize renal lesions without contrast media, but these techniques warrant further investigation. PET may be a useful tool for evaluating patients with suspected metastatic disease, but it has modest sensitivity in the diagnosis and staging of RCC. The newer radiotracers may increase the accuracy of PET for RCC diagnosis and staging. In summary, the main imaging modality used for the characterization, staging, and surveillance of RCC is multiphasic CT. Other imaging modalities, such as MRI and PET, are used for selected indications.

HRCT Diagnosis of Pleuroparenchymal fibroelastosis: Report of two cases.

Pleuroparenchymal fibroelastosis (PPFE) is a rare idiopathic interstitial pneumonia that is often underdiagnosed on computed tomography scans. The disease process involves a combination of fibrosis involving the visceral pleura and fibroelastic changes within the subpleural lung parenchyma. Although definitive diagnosis is based on pathological evaluation, this is often not feasible and pattern recognition on CT as "definite PPFE" or "consistent with PPFE" is important given that sub group of patients will undergo rapid progression with clinical deterioration.

Pediatric spinal cord infarction following a minor trauma: a case report.

INTRODUCTION: Pediatric spinal cord infarction is a rare entity that presents a diagnostic challenge at the emergency department. Ischemic spinal cord infarction can occur in the setting of trauma, cardiovascular malformation, or postoperatively. We report a case of anterior spinal artery infarction following seemingly minor trauma in an otherwise healthy 14-year-old male. CASE PRESENTATION: A 14-year-old male presented with unprovoked sudden-onset stabbing back pain earlier that day. The patient then demonstrated bilateral lower extremities weakness while at the emergency department. After extensive diagnostic workup, the patient was diagnosed with anterior spinal artery territory infarction involving the thoracic spinal cord. Minor trauma to the thoracic spinal cord was detected on imaging and was believed to be the culprit of this event. DISCUSSION: Given the rarity of spinal cord ischemia, a high index of suspicion and extensive workup of patients presenting with clinical weakness are needed for accurate diagnosis and to avoid the eventual poor outcome. With so few reports in the literature regarding spinal cord ischemia in the pediatric population, accurate diagnosis is often delayed until after irreversible events have already taken place. Our case report of anterior spinal artery distribution thoracic cord infarct following a minor trauma was diagnosed by axial thin-slice DWI MRI with an otherwise negative workup.

Adrenal cortical carcinoma: pathology, genomics, prognosis, imaging features, and mimics with impact on management.

Adrenocortical carcinoma (ACC) is a rare tumor with a poor prognosis. Most tumors are either metastatic or locally invasive at the time of diagnosis. Differentiation between ACC and other adrenal masses depends on clinical, biochemical, and imaging factors. This review will discuss the genetics, pathological, and imaging feature of ACC.

A machine learning model to predict hepatocellular carcinoma response to transcatheter arterial chemoembolization.

PURPOSE: Some patients with hepatocellular carcinoma (HCC) are more likely to experience disease progression despite transcatheter arterial chemoembolization (TACE) treatment, and thus would benefit from early switching to other therapeutic regimens. We sought to evaluate a fully automated machine learning algorithm that uses pre-therapeutic quantitative computed tomography (CT) image features and clinical factors to predict HCC response to TACE. MATERIALS AND METHODS: Outcome information from 105 patients receiving first-line treatment with TACE was evaluated retrospectively. The primary clinical endpoint was time to progression (TTP) based on follow-up CT radiological criteria (mRECIST). A 14-week cutoff was used to classify patients as TACE-susceptible (TTP ≥14 weeks) or TACE-refractory (TTP <14 weeks). Response to TACE was predicted using a random forest classifier with the Barcelona Clinic Liver Cancer (BCLC) stage and quantitative image features as input as well as the BCLC stage alone as a control. RESULTS: The model's response prediction accuracy rate was 74.2% (95% CI=64%-82%) using a combination of the BCLC stage plus quantitative image features versus 62.9% (95% CI= 52%-72%) using the BCLC stage alone. Shape image features of the tumor and background liver were the dominant features correlated to the TTP as selected by the Boruta method and were used to predict the outcome. CONCLUSION: This preliminary study demonstrates that quantitative image features obtained prior to therapy can improve the accuracy of predicting response of HCC to TACE. This approach is likely to provide useful information for aiding HCC patient selection for TACE.

LI-RADS: a conceptual and historical review from its beginning to its recent integration into AASLD clinical practice guidance.

The Liver Imaging Reporting and Data System (LI-RADS®) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver observations in individuals at high risk for hepatocellular carcinoma (HCC). LI-RADS is supported and endorsed by the American College of Radiology (ACR). Upon its initial release in 2011, LI-RADS applied only to liver observations identified at CT or MRI. It has since been refined and expanded over multiple updates to now also address ultrasound-based surveillance, contrast-enhanced ultrasound for HCC diagnosis, and CT/MRI for assessing treatment response after locoregional therapy. The LI-RADS 2018 version was integrated into the HCC diagnosis, staging, and management practice guidance of the American Association for the Study of Liver Diseases (AASLD). This article reviews the major LI-RADS updates since its 2011 inception and provides an overview of the currently published LI-RADS algorithms.

Role of Wnt/ß-catenin signaling in hepatocellular carcinoma, pathogenesis, and clinical significance.

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies and one of the fastest-growing causes of cancer-related mortality in the United States. The molecular basis of HCC carcinogenesis has not been clearly identified. Among the molecular signaling pathways implicated in the pathogenesis of HCC, the Wnt/ß-catenin signaling pathway is one of the most frequently activated. A great effort is under way to clearly understand the role of this pathway in the pathogenesis of HCC and its role in the transition from chronic liver diseases, including viral hepatitis, to hepatocellular adenomas (HCAs) and HCCs and its targetability in novel therapies. In this article, we review the role of the ß-catenin pathway in hepatocarcinogenesis and progression from chronic inflammation to HCC, the novel potential treatments targeting the pathway and its prognostic role in HCC patients, as well as the imaging features of HCC and their association with aberrant activation of the pathway.