Changing Abdominal Imaging Utilization Patterns: Perspectives From Medicare Beneficiaries Over Two Decades

Post-contrast CT liver attenuation alone is superior to the liver-spleen difference for identifying moderate hepatic steatosis

OBJECTIVE

To assess the diagnostic performance of post-contrast CT for predicting moderate hepatic steatosis in an older adult cohort undergoing a uniform CT protocol, utilizing hepatic and splenic attenuation values.

MATERIALS AND METHODS

A total of 1676 adults (mean age, 68.4 ± 10.2 years; 1045M/631F) underwent a CT urothelial protocol that included unenhanced, portal venous, and 10-min delayed phases through the liver and spleen. Automated hepatosplenic segmentation for attenuation values (in HU) was performed using a validated deep-learning tool. Unenhanced liver attenuation < 40.0 HU, corresponding to > 15% MRI-based proton density fat, served as the reference standard for moderate steatosis.

RESULTS

The prevalence of moderate or severe steatosis was 12.9% (216/1676). The diagnostic performance of portal venous liver HU in predicting moderate hepatic steatosis (AUROC = 0.943) was significantly better than the liver-spleen HU difference (AUROC = 0.814) (p < 0.001). Portal venous phase liver thresholds of 80 and 90 HU had a sensitivity/specificity for moderate steatosis of 85.6%/89.6%, and 94.9%/74.7%, respectively, whereas a liver-spleen difference of -40 HU and -10 HU had a sensitivity/specificity of 43.5%/90.0% and 92.1%/52.5%, respectively. Furthermore, livers with moderate-severe steatosis demonstrated significantly less post-contrast enhancement (mean, 35.7 HU vs 47.3 HU; p < 0.001).

CONCLUSION

Moderate steatosis can be reliably diagnosed on standard portal venous phase CT using liver attenuation values alone. Consideration of splenic attenuation appears to add little value. Moderate steatosis not only has intrinsically lower pre-contrast liver attenuation values (< 40 HU), but also enhances less, typically resulting in post-contrast liver attenuation values of 80 HU or less.

CLINICAL RELEVANCE STATEMENT

Moderate steatosis can be reliably diagnosed on post-contrast CT using liver attenuation values alone. Livers with at least moderate steatosis enhance less than those with mild or no steatosis, which combines with the lower intrinsic attenuation to improve detection.

KEY POINTS

The liver-spleen attenuation difference is frequently utilized in routine practice but appears to have performance limitations. The liver-spleen attenuation difference is less effective than liver attenuation for moderate steatosis. Moderate and severe steatosis can be identified on standard portal venous phase CT using liver attenuation alone.

Older Tissue Age Derived From Abdominal Computed Tomography Biomarkers of Muscle, Fat, and Bone Is Associated With Chronic Conditions and Higher Mortality

OBJECTIVE

To determine whether body composition derived from medical imaging may be useful for assessing biologic age at the tissue level because people of the same chronologic age may vary with respect to their biologic age.

METHODS

We identified an age- and sex-stratified cohort of 4900 persons with an abdominal computed tomography scan from January 1, 2010, to December 31, 2020, who were 20 to 89 years old and representative of the general population in Southeast Minnesota and West Central Wisconsin. We constructed a model for estimating tissue age that included 6 body composition biomarkers calculated from abdominal computed tomography using a previously validated deep learning model.

RESULTS

Older tissue age associated with intermediate subcutaneous fat area, higher visceral fat area, lower muscle area, lower muscle density, higher bone area, and lower bone density. A tissue age older than chronologic age was associated with chronic conditions that result in reduced physical fitness (including chronic obstructive pulmonary disease, arthritis, cardiovascular disease, and behavioral disorders). Furthermore, a tissue age older than chronologic age was associated with an increased risk of death (hazard ratio, 1.56; 95% CI, 1.33 to 1.84) that was independent of demographic characteristics, county of residency, education, body mass index, and baseline chronic conditions.

CONCLUSION

Imaging-based body composition measures may be useful in understanding the biologic processes underlying accelerated aging.

Detection of Moderate Hepatic Steatosis on Portal Venous Phase Contrast-Enhanced CT: Evaluation Using an Automated Artificial Intelligence Tool

BACKGROUND. Precontrast CT is an established means of evaluating for hepatic steatosis; postcontrast CT has historically been limited for this purpose. OBJECTIVE. The purpose of this study was to evaluate the diagnostic performance of portal venous phase postcontrast CT in detecting at least moderate hepatic steatosis using liver and spleen attenuation measurements determined by an automated artificial intelligence (AI) tool. METHODS. This retrospective study included 2917 patients (1381 men, 1536 women; mean age, 56.8 years) who underwent a CT examination that included at least two series through the liver. Examinations were obtained from an AI vendor's data lake of data from 24 centers in one U.S. health care network and 29 centers in one Israeli health care network. An automated deep learning tool extracted liver and spleen attenuation measurements. The reference for at least moderate steatosis was precontrast liver attenuation of less than 40 HU (i.e., estimated liver fat > 15%). A radiologist manually reviewed examinations with outlier AI results to confirm portal venous timing and identify issues impacting attenuation measurements. RESULTS. After outlier review, analysis included 2777 patients with portal venous phase images. Prevalence of at least moderate steatosis was 13.9% (387/2777). Patients without and with at least moderate steatosis, respectively, had mean postcontrast liver attenuation of 104.5 ± 18.1 (SD) HU and 67.1 ± 18.6 HU (p < .001); a mean difference in postcontrast attenuation between the liver and the spleen (hereafter, postcontrast liver-spleen attenuation difference) of -7.6 ± 16.4 (SD) HU and -31.8 ± 20.3 HU (p < .001); and mean liver enhancement of 49.3 ± 15.9 (SD) HU versus 38.6 ± 13.6 HU (p < .001). Diagnostic performance for the detection of at least moderate steatosis was higher for postcontrast liver attenuation (AUC = 0.938) than for the postcontrast liver-spleen attenuation difference (AUC = 0.832) (p < .001). For detection of at least moderate steatosis, postcontrast liver attenuation had sensitivity and specificity of 77.8% and 93.2%, respectively, at less than 80 HU and 90.5% and 78.4%, respectively, at less than 90 HU; the postcontrast liver-spleen attenuation difference had sensitivity and specificity of 71.4% and 79.3%, respectively, at less than -20 HU and 87.0% and 62.1%, respectively, at less than -10 HU. CONCLUSION. Postcontrast liver attenuation outperformed the postcontrast liver-spleen attenuation difference for detecting at least moderate steatosis in a heterogeneous patient sample, as evaluated using an automated AI tool. Splenic attenuation likely is not needed to assess for at least moderate steatosis on postcontrast images. CLINICAL IMPACT. The technique could promote early detection of clinically significant nonalcoholic fatty liver disease through individualized or large-scale opportunistic evaluation.

CT-based methods for assessment of metabolic dysfunction associated with fatty liver disease

Metabolic dysfunction-associated fatty liver disease (MAFLD), previously called metabolic nonalcoholic fatty liver disease, is the most prevalent chronic liver disease worldwide. The multi-factorial nature of MAFLD severity is delineated through an intricate composite analysis of the grade of activity in concert with the stage of fibrosis. Despite the preeminence of liver biopsy as the diagnostic and staging reference standard, its invasive nature, pronounced interobserver variability, and potential for deleterious effects (encompassing pain, infection, and even fatality) underscore the need for viable alternatives. We reviewed computed tomography (CT)-based methods for hepatic steatosis quantification (liver-to-spleen ratio; single-energy "quantitative" CT; dual-energy CT; deep learning-based methods; photon-counting CT) and hepatic fibrosis staging (morphology-based CT methods; contrast-enhanced CT biomarkers; dedicated postprocessing methods including liver surface nodularity, liver segmental volume ratio, texture analysis, deep learning methods, and radiomics). For dual-energy and photon-counting CT, the role of virtual non-contrast images and material decomposition is illustrated. For contrast-enhanced CT, normalized iodine concentration and extracellular volume fraction are explained. The applicability and salience of these approaches for clinical diagnosis and quantification of MAFLD are discussed.Relevance statementCT offers a variety of methods for the assessment of metabolic dysfunction-associated fatty liver disease by quantifying steatosis and staging fibrosis.Key points• MAFLD is the most prevalent chronic liver disease worldwide and is rapidly increasing.• Both hardware and software CT advances with high potential for MAFLD assessment have been observed in the last two decades.• Effective estimate of liver steatosis and staging of liver fibrosis can be possible through CT.

How Do Cancer-Specific Computed Tomography Protocols Compare With the American College of Radiology Dose Index Registry? An Analysis of Computed Tomography Dose at 2 Cancer Centers

BACKGROUND

Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey.

METHODS

A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2.

RESULTS

Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology.

CONCLUSIONS

We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

Temporal trends in ultrasound utilisation in the radiology department of a tertiary hospital

Background: Little is known about the combined impact of increasing ultrasound usage by clinical disciplines outside radiology and technical advances in other specialised radiological modalities on the role of ultrasound in tertiary-level radiology departments.Objectives: The aim of this study was to evaluate temporal trends in ultrasound utilisation in a tertiary-level radiology department.Method: An institutional review board-approved retrospective descriptive study in the radiology department of Tygerberg Hospital (TBH). The nature and number of ultrasound performed in 2013 and 2019 were retrieved from the TBH radiology information system (RIS). These were compared, expressed as a proportion of the overall annual radiology workload and stratified by location (ultrasound suite, interventional suite, mammography suite). Ultrasound suite examinations were analysed by body part and age (0–13 years; 13 years) and interventional suite workload by procedure.Results: The overall radiology workload decreased by 8%, reflecting the interplay between decreased plain radiography (–19%) and general fluoroscopy (–0.3%) and increased computed tomography (27%), magnetic resonance (23%) and fluoroscopically guided procedures (22%).There was a 12% increase in ultrasound utilisation. Ultrasound remained the second most common specialised imaging investigation throughout, after computed tomography. Ultrasound suite services were stable (–1%) representing a balance between decreased abdominal (–22%) and arterial (–16%) scans, and increased musculoskeletal (67%), small part (65%) and neonatal brain scans (41%). There were substantial increases in interventional (90%) and mammography suite (199%) services.Conclusion: Ultrasound remains a key modality in the tertiary-level radiology department, with an evolving pattern of clinical applications.

Evaluation of radiomics and machine learning in identification of aggressive tumor features in renal cell carcinoma (RCC)

PURPOSE

The purpose of this study was to evaluate the use of CT radiomics features and machine learning analysis to identify aggressive tumor features, including high nuclear grade (NG) and sarcomatoid (sarc) features, in large renal cell carcinomas (RCCs).

METHODS

CT-based volumetric radiomics analysis was performed on non-contrast (NC) and portal venous (PV) phase multidetector computed tomography images of large (> 7 cm) untreated RCCs in 141 patients (46W/95M, mean age 60 years). Machine learning analysis was applied to the extracted radiomics data to evaluate for association with high NG (grade 3-4), with multichannel analysis for NG performed in a subset of patients (n = 80). A similar analysis was performed in a sarcomatoid rich cohort (n = 43, 31M/12F, mean age 63.7 years) using size-matched non-sarcomatoid controls (n = 49) for identification of sarcomatoid change.

RESULTS

The XG Boost Model performed best on the tested data. After manual and machine feature extraction, models consisted of 3, 7, 5, 10 radiomics features for NC sarc, PV sarc, NC NG and PV NG, respectively. The area under the receiver operating characteristic curve (AUC) for these models was 0.59, 0.65, 0.69 and 0.58 respectively. The multichannel NG model extracted 6 radiomic features using the feature selection strategy and showed an AUC of 0.67.

CONCLUSIONS

Statistically significant but weak associations between aggressive tumor features (high nuclear grade, sarcomatoid features) in large RCC were identified using 3D radiomics and machine learning analysis.

Multisite multivendor validation of a quantitative MRI and CT compatible fat phantom

PURPOSE

Chemical shift-encoded magnetic resonance imaging enables accurate quantification of liver fat content though estimation of proton density fat-fraction (PDFF). Computed tomography (CT) is capable of quantifying fat, based on decreased attenuation with increased fat concentration. Current quantitative fat phantoms do not accurately mimic the CT number of human liver. The purpose of this work was to develop and validate an optimized phantom that simultaneously mimics the MRI and CT signals of fatty liver.

METHODS

An agar-based phantom containing 12 vials doped with iodinated contrast, and with a granular range of fat fractions was designed and constructed within a novel CT and MR compatible spherical housing design. A four-site, three-vendor validation study was performed. MRI (1.5T and 3T) and CT images were obtained using each vendor's PDFF and CT reconstruction, respectively. An ROI centered in each vial was placed to measure MRI-PDFF (%) and CT number (HU). Mixed-effects model, linear regression, and Bland-Altman analysis were used for statistical analysis.

RESULTS

MRI-PDFF agreed closely with nominal PDFF values across both field strengths and all MRI vendors. A linear relationship (slope = -0.54 ± 0.01%/HU, intercept = 37.15 ± 0.03%) with an R² of 0.999 was observed between MRI-PDFF and CT number, replicating established in vivo signal behavior. Excellent test-retest repeatability across vendors (MRI: mean = -0.04%, 95% limits of agreement = [-0.24%, 0.16%]; CT: mean = 0.16 HU, 95% limits of agreement = [-0.15HU, 0.47HU]) and good reproducibility using GE scanners (MRI: mean = -0.21%, 95% limits of agreement = [-1.47%, 1.06%]; CT: mean = -0.18HU, 95% limits of agreement = [-1.96HU, 1.6HU]) were demonstrated.

CONCLUSIONS

The proposed fat phantom successfully mimicked quantitative liver signal for both MRI and CT. The proposed fat phantom in this study may facilitate broader application and harmonization of liver fat quantification techniques using MRI and CT across institutions, vendors and imaging platforms.

Automated assessment of longitudinal biomarker changes at abdominal CT: correlation with subsequent cardiovascular events in an asymptomatic adult screening cohort

BACKGROUND

Cardiovascular (CV) disease is a major public health concern, and automated methods can potentially capture relevant longitudinal changes on CT for opportunistic CV screening purposes.

METHODS

Fully-automated and validated algorithms that quantify abdominal fat, muscle, bone, liver, and aortic calcium were retrospectively applied to a longitudinal adult screening cohort undergoing serial non-contrast CT examination between 2005 and 2016. Downstream major adverse events (MI/CVA/CHF/death) were identified via algorithmic EHR search. Logistic regression, ROC curve, and Cox survival analyses assessed for associations between changes in CT variables and adverse events.

RESULTS

Final cohort included 1949 adults (942 M/1007F; mean age, 56.2 ± 6.2 years at initial CT). Mean interval between CT scans was 5.8 ± 2.0 years. Mean clinical follow-up interval from initial CT was 10.4 ± 2.7 years. Major CV events occurred after follow-up CT in 230 total subjects (11.8%). Mean change in aortic calcium Agatston score was significantly higher in CV(+) cohort (591.6 ± 1095.3 vs. 261.1 ± 764.3), as was annualized Agatston change (120.5 ± 263.6 vs. 46.7 ± 143.9) (p < 0.001 for both). 5-year area under the ROC curve (AUC) for Agatston change was 0.611. Hazard ratio for Agatston score change > 500 was 2.8 (95% CI 1.5-4.0) relative to < 500. Agatston score change was the only significant univariate CT biomarker in the survival analysis. Changes in fat and bone measures added no meaningful prediction.

CONCLUSION

Interval change in automated CT-based abdominal aortic calcium load represents a promising predictive longitudinal tool for assessing cardiovascular and mortality risks. Changes in other body composition measures were less predictive of adverse events.

Revisiting Cushing Syndrome, Milder Forms Are Now a Common Occurrence: A Single-Center Cohort of 76 Subjects

OBJECTIVE

Guidelines recommend initiating testing for Cushing syndrome (CS) based on strong clinical suspicion. Our recent experience suggests the absence of classical stigmata in the majority of patients with CS. We aimed to confirm this premise by revisiting the clinical features of this syndrome in a modern series of patients from a single center.

METHODS

Computerized records of subjects with CS diagnosed at Tel Aviv Sourasky Medical Center between 2000 and 2018 were reviewed. A Cushing inventory score, including all clinical components of the syndrome, was computed for each subject. Data were compared between the subtypes and evaluated in light of those in the literature.

RESULTS

Of the 76 subjects with CS (60 women/16 men), 49 (64.5%) had Cushing disease; 16 (21.1%), adrenal adenoma; 7 (9.2%), adrenocortical carcinoma; and 4 (5.3%), ectopic adrenocorticotropic hormone secretion. In only 15 of 74 cases (20.3%), clinical suspicion of CS led to testing. Catabolic signs of CS were present in less than 30% of cases. The most common symptom was weight gain (52/67, 77.6%), and the most common comorbidity was hypertension (47/76, 61.8%). There were no differences in the Cushing inventory score between the subtypes. Signs, symptoms, and comorbidities were all significantly less common than in the classical syndrome.

CONCLUSIONS

Modern-day CS presents with subtler features than in the past. Initiating a testing cascade solely based on a strong clinical suspicion may lead to underdiagnosis of milder cases. A concerted effort to devise cost-efficient testing for CS in the current era is needed.

Role of Multimodality Imaging in Gastroesophageal Reflux Disease and Its Complications, with Clinical and Pathologic Correlation

Gastroesophageal reflux disease (GERD) is a common condition and impairs the quality of life for millions of patients, accounts for considerable health care spending, and is a primary risk factor for esophageal adenocarcinoma. There have been substantial advances in understanding the pathogenesis of GERD and its complications and much progress in diagnosis and management of GERD; however, these have not been comprehensively discussed in the recent radiology literature. Understanding the role of imaging in GERD and its complications is important to aid in multidisciplinary treatment of GERD. GERD results from prolonged or recurrent reflux of gastric contents into the esophagus. Common symptoms include heartburn or regurgitation. Prolonged reflux of gastric contents into the esophagus can cause erosive esophagitis. Over time, the inflammatory response related to esophagitis can lead to deposition of fibrous tissue and development of strictures. Alternatively, the esophageal mucosa can undergo metaplasia (Barrett esophagus), a precursor to dysplasia (which can lead to adenocarcinoma). Conventional barium esophagography has long been considered the primary imaging modality for the esophagus, and the fluoroscopic findings for diagnosis of GERD have been well established. Multimodality imaging has a clear role in detection and assessment of the complications of GERD, specifically reflux esophagitis and Barrett esophagus; differentiation of benign and malignant strictures; and detection, staging, and posttreatment surveillance of esophageal adenocarcinoma. Given the dramatic changes in utilization of abdominal imaging during the past 2 decades, with significantly declining volume of fluoroscopic procedures and concomitant increase in CT and MRI studies, it is crucial that modern radiologists appreciate the value of barium esophagography in the workup of GERD and recognize the key imaging features of GERD and its complications at CT and MRI.

Utility of Multiparametric CT for Identification of High-Risk NAFLD

OBJECTIVE. The purpose of this study was to evaluate the utility of laboratory and CT metrics in identifying patients with high-risk nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS. Patients with biopsy-proven NAFLD who underwent CT within 1 year of biopsy were included. Histopathologic review was performed by an experienced gastrointestinal pathologist to determine steatosis, inflammation, and fibrosis. The presence of any lobular inflammation and hepatocyte ballooning was categorized as nonalcoholic steatohepatitis (NASH). Patients with NAFLD and advanced fibrosis (stage F3 or higher) were categorized as having high-risk NAFLD. Aspartate transaminase to platelet ratio index and Fibrosis-4 (FIB-4) laboratory scores were calculated. CT metrics included hepatic attenuation, liver segmental volume ratio (LSVR), splenic volume, liver surface nodularity score, and selected texture features. In addition, two readers subjectively assessed the presence of NASH (present or not present) and fibrosis (stages F0-F4). RESULTS. A total of 186 patients with NAFLD (mean age, 49 years; 74 men and 112 women) were included. Of these, 87 (47%) had NASH and 112 (60%) had moderate to severe steatosis. A total of 51 patients were classified as fibrosis stage F0, 42 as F1, 23 as F2, 37 as F3, and 33 as F4. Additionally, 70 (38%) had advanced fibrosis (stage F3 or F4) and were considered to have high-risk NAFLD. FIB-4 score correlated with fibrosis (ROC AUC of 0.75 for identifying high-risk NAFLD). Of the individual CT parameters, LSVR and splenic volume performed best (AUC of 0.69 for both for detecting high-risk NAFLD). Subjective reader assessment performed best among all parameters (AUCs of 0.78 for reader 1 and 0.79 for reader 2 for detecting high-risk NAFLD). FIB-4 and subjective scores were complementary (combined AUC of 0.82 for detecting high-risk NAFLD). For NASH assessment, FIB-4 performed best (AUC of 0.68), whereas the AUCs were less than 0.60 for all individual CT features and subjective assessments. CONCLUSION. FIB-4 and multiple CT findings can identify patients with high-risk NAFLD (advanced fibrosis or cirrhosis). However, the presence of NASH is elusive on CT.

Impact of novel deep learning image reconstruction algorithm on diagnosis of contrast-enhanced liver computed tomography imaging: Comparing to adaptive statistical iterative reconstruction algorithm

OBJECTIVE

To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with using adaptive statistical iterative reconstruction (ASIR-V) algorithm under routine dose.

METHODS

The raw data from 42 consecutive patients who underwent contrast-enhanced portal venous phase liver CT were reconstructed using three strength levels of DLIRs (low [DL-L]; medium [DL-M]; high [DL-H]) and two levels of ASIR-V (30%[AV-30]; 70%[AV-70]). Objective image parameters, including noise, signal-to-noise (SNR), and the contrast-to-noise ratio (CNR) relative to muscle, as well as subjective parameters, including noise, artifact, hepatic vein-clarity, index lesion-clarity, and overall scores were compared pairwise. For the lesions detection rate, the five reconstructions in patients who underwent subsequent contrast-enhanced magnetic resonance imaging (MRI) examinations were compared.

RESULTS

For objective parameters, DL-H exhibited superior image quality of lower noise and higher SNR than AV-30 and AV-70 (all P < 0.05). CNR was not statistically different between AV-70, DL-M, and DL-H (all P > 0.05). In both objective and subjective parameters, only image noise was statistically reduced as the strength of DLIR increased compared with ASIR-V (all P < 0.05). Regarding the lesions detection rate, a total of 45 lesions were detected by MRI examination and all five reconstructions exhibited similar lesion-detection rate (25/45, 55.6%).

CONCLUSION

Compared with AV-30 and AV 70, DLIR leads to better image quality with equal lesion detection rate for liver CT imaging under routine dose.

Incidental biliary dilation in the era of the opiate epidemic: High prevalence of biliary dilation in opiate users evaluated in the Emergency Department

BACKGROUND

Biliary dilation is frequently related to obstruction; however, non-obstructive factors such as age and previous cholecystectomy have also been reported. In the past two decades there has been a dramatic increase in opiate use/dependence and utilization of cross-sectional abdominal imaging, with increased detection of biliary dilation, particularly in patients who use opiates.

AIM

To evaluate associations between opiate use, age, cholecystectomy status, ethnicity, gender, and body mass index utilizing our institution’s integrated informatics platform.

METHODS

One thousand six hundred and eighty-five patients (20% sample) presenting to our Emergency Department for all causes over a 5-year period (2011-2016) who had undergone cross-sectional abdominal imaging and had normal total bilirubin were included and analyzed.

RESULTS

Common bile duct (CBD) diameter was significantly higher in opiate users compared to non-opiate users (8.67 mm vs 7.24 mm, P < 0.001) and in patients with a history of cholecystectomy compared to those with an intact gallbladder (8.98 vs 6.72, P < 0.001). For patients with an intact gallbladder who did not use opiates (n = 432), increasing age did not predict CBD diameter (r² = 0.159, P = 0.873). Height weakly predicted CBD diameter (r² = 0.561, P = 0.018), but weight, body mass index, ethnicity and gender did not.

CONCLUSION

Opiate use and a history of cholecystectomy are associated with CBD dilation in the absence of an obstructive process. Age alone is not associated with increased CBD diameter. These findings suggest that factors such as opiate use and history of cholecystectomy may underlie the previously-reported association of advancing age with increased CBD diameter. Further prospective study is warranted.

Automated Abdominal CT Imaging Biomarkers for Opportunistic Prediction of Future Major Osteoporotic Fractures in Asymptomatic Adults

Background Body composition data from abdominal CT scans have the potential to opportunistically identify those at risk for future fracture. Purpose To apply automated bone, muscle, and fat tools to noncontrast CT to assess performance for predicting major osteoporotic fractures and to compare with the Fracture Risk Assessment Tool (FRAX) reference standard. Materials and Methods Fully automated bone attenuation (L1-level attenuation), muscle attenuation (L3-level attenuation), and fat (L1-level visceral-to-subcutaneous [V/S] ratio) measures were derived from noncontrast low-dose abdominal CT scans in a generally healthy asymptomatic adult outpatient cohort from 2004 to 2016. The FRAX score was calculated from data derived from an algorithmic electronic health record search. The cohort was assessed for subsequent future fragility fractures. Subset analysis was performed for patients evaluated with dual x-ray absorptiometry (n = 2106). Hazard ratios (HRs) and receiver operating characteristic curve analyses were performed. Results A total of 9223 adults were evaluated (mean age, 57 years ± 8 [standard deviation]; 5152 women) at CT and were followed over a median time of 8.8 years (interquartile range, 5.1-11.6 years), with documented subsequent major osteoporotic fractures in 7.4% (n = 686), including hip fractures in 2.4% (n = 219). Comparing the highest-risk quartile with the other three quartiles, HRs for bone attenuation, muscle attenuation, V/S fat ratio, and FRAX were 2.1, 1.9, 0.98, and 2.5 for any fragility fracture and 2.0, 2.5, 1.1, and 2.5 for femoral fractures, respectively (P < .001 for all except V/S ratio, which was P ≥ .51). Area under the receiver operating characteristic curve (AUC) values for fragility fracture were 0.71, 0.65, 0.51, and 0.72 at 2 years and 0.63, 0.62, 0.52, and 0.65 at 10 years, respectively. For hip fractures, 2-year AUC for muscle attenuation alone was 0.75 compared with 0.73 for FRAX (P = .43). Multivariable 2-year AUC combining bone and muscle attenuation was 0.73 for any fragility fracture and 0.76 for hip fractures, respectively (P ≥ .73 compared with FRAX). For the subset with dual x-ray absorptiometry T-scores, 2-year AUC was 0.74 for bone attenuation and 0.65 for FRAX (P = .11). Conclusion Automated bone and muscle imaging biomarkers derived from CT scans provided comparable performance to Fracture Risk Assessment Tool score for presymptomatic prediction of future osteoporotic fractures. Muscle attenuation alone provided effective hip fracture prediction. © RSNA, 2020 See also the editorial by Smith in this issue.

Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard

BACKGROUND. Hepatic attenuation at unenhanced CT is linearly correlated with the MRI proton density fat fraction (PDFF). Liver fat quantification at contrast-enhanced CT is more challenging. OBJECTIVE. The purpose of this article is to evaluate liver steatosis categorization on contrast-enhanced CT using a fully automated deep learning volumetric hepatosplenic segmentation algorithm and unenhanced CT as the reference standard. METHODS. A fully automated volumetric hepatosplenic segmentation algorithm using 3D convolutional neural networks was applied to unenhanced and contrast-enhanced series from a sample of 1204 healthy adults (mean age, 45.2 years; 726 women, 478 men) undergoing CT evaluation for renal donation. The mean volumetric attenuation was computed from all designated liver and spleen voxels. PDFF was estimated from unenhanced CT attenuation and served as the reference standard. Contrast-enhanced attenuations were evaluated for detecting PDFF thresholds of 5% (mild steatosis, 10% and 15% (moderate steatosis); PDFF less than 5% was considered normal. RESULTS. Using unenhanced CT as reference, estimated PDFF was ≥ 5% (mild steatosis), ≥ 10%, and ≥ 15% (moderate steatosis) in 50.1% (n = 603), 12.5% (n = 151) and 4.8% (n = 58) of patients, respectively. ROC AUC values for predicting PDFF thresholds of 5%, 10%, and 15% using contrast-enhanced liver attenuation were 0.669, 0.854, and 0.962, respectively, and using contrast-enhanced liver-spleen attenuation difference were 0.662, 0.866, and 0.986, respectively. A total of 96.8% (90/93) of patients with contrast-enhanced liver attenuation less than 90 HU had steatosis (PDFF ≥ 5%); this threshold of less than 90 HU achieved sensitivity of 75.9% and specificity of 95.7% for moderate steatosis (PDFF ≥ 15%). Liver attenuation less than 100 HU achieved sensitivity of 34.0% and specificity of 94.2% for any steatosis (PDFF ≥ 5%). A total of 93.8% (30/32) of patients with contrast-enhanced liver-spleen attenuation difference 10 HU or less had moderate steatosis (PDFF ≥ 15%); a liver-spleen difference less than 5 HU achieved sensitivity of 91.4% and specificity of 95.0% for moderate steatosis. Liver-spleen difference less than 10 HU achieved sensitivity of 29.5% and specificity of 95.5% for any steatosis (PDFF ≥ 5%). CONCLUSION. Contrast-enhanced volumetric hepatosplenic attenuation derived using a fully automated deep learning CT tool may allow objective categoric assessment of hepatic steatosis. Accuracy was better for moderate than mild steatosis. Further confirmation using different scanning protocols and vendors is warranted. CLINICAL IMPACT. If these results are confirmed in independent patient samples, this automated approach could prove useful for both individualized and population-based steatosis assessment.

Radiomics and Artificial Intelligence for Renal Mass Characterization

Radiomics allows for high throughput extraction of quantitative data from images. This is an area of active research as groups try to capture and quantify imaging parameters and convert these into descriptive phenotypes of organs or tumors. Texture analysis is one radiomics tool that extracts information about heterogeneity within a given region of interest. This is used with or without associated machine learning classifiers or a deep learning approach is applied to similar types of data. These tools have shown utility in characterizing renal masses, renal cell carcinoma, and assessing response to targeted therapeutic agents in metastatic renal cell carcinoma.

Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience

OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. MATERIALS AND METHODS. Retrospective review (April-May 2019) of the cases of adults undergoing oncologic staging with portal venous phase abdominal CT was conducted for evaluation of standard 30% adaptive statistical iterative reconstruction V (30% ASIR-V) reconstruction compared with DLIR at low, medium, and high strengths. Attenuation and noise measurements were performed. Two radiologists, blinded to examination details, scored six categories while comparing reconstructions for overall image quality, lesion diagnostic confidence, artifacts, image noise and texture, lesion conspicuity, and resolution. RESULTS. DLIR had a better contrast-to-noise ratio than 30% ASIR-V did; high-strength DLIR performed the best. High-strength DLIR was associated with 47% reduction in noise, resulting in a 92-94% increase in contrast-to-noise ratio compared with that of 30% ASIR-V. For overall image quality and image noise and texture, DLIR scored significantly higher than 30% ASIR-V with significantly higher scores as DLIR strength increased. A total of 193 lesions were identified. The lesion diagnostic confidence, conspicuity, and artifact scores were significantly higher for all DLIR levels than for 30% ASIR-V. There was no significant difference in perceived resolution between the reconstruction methods. CONCLUSION. Compared with 30% ASIR-V, DLIR improved CT evaluation of the abdomen in the portal venous phase. DLIR strength should be chosen to balance the degree of desired denoising for a clinical task relative to mild blurring, which increases with progressively higher DLIR strengths.

Changes in Current Procedural Terminology Coding and Its Effect on Specialty-Level Utilization of Musculoskeletal Ultrasound

PURPOSE

Concerns regarding increasing utilization of non-vascular extremity ultrasound (US) imaging led to the Current Procedural Terminology (CPT) Editorial Panel separating a singular billing code into distinct comprehensive and focused examination codes with differential reimbursement. We explore this policy change's temporal association with utilization.

METHODS

Using Physician/Supplier Procedure Summary Master Files, we identified all nonvascular extremity US services billed for Medicare fee-for-service beneficiaries between 1994 and 2017. These included generic (CPT code 76880 from 1994 to 2010), complete (code 76881 from 2011 to 2017), and limited (code 76882 from 2011 to 2017) examinations. Annual utilization per 100,000 beneficiaries was computed and stratified by billing specialty. Compound annual growth rates were calculated.

RESULTS

Radiologists and podiatrists were the top 2 billing specialties for nonvascular extremity US examinations. From 1994 to 2010, radiologist services increased 6.1% annually. Following the 2011 code separation, radiologists' utilization increased 2.7% annually for complete and 12.3% for limited exams. Between 1994 and 2017, radiologists' market share decreased 72.8% to 40.4%. From 1994 to 2010, podiatrist services increased 87.1% annually. Following the code separation, podiatrists' annual utilization growth stabilized 0.4% for complete and 0.6% for limited exams. Podiatrists' market share was 9.1% in 2001, peaked at 31.3% in 2009, and declined to 14.3% in 2017.

CONCLUSIONS

Prior rapid growth in extremity nonvascular US for podiatrists slowed considerably following CPT code separation in 2011. Subsequent service growth has largely been related to less costly, focused examinations performed by radiologists. Further study may help better understand how CPT coding changes alter imaging utilization more broadly.

Achieving CT Regulatory Compliance: A Comprehensive and Continuous Quality Improvement Approach

Computed tomography (CT) represents one of the largest sources of radiation exposure to the public in the United States. Regulatory requirements now mandate dose tracking for all exams and investigation of dose events that exceed set dose thresholds. Radiology practices are tasked with ensuring quality control and optimizing patient CT exam doses while maintaining diagnostic efficacy. Meeting regulatory requirements necessitates the development of an effective quality program in CT. This review provides a template for accreditation compliant quality control and CT dose optimization. The following paper summarizes a large health system approach for establishing a quality program in CT and discusses successes, challenges, and future needs.

Impact of Overlying Personal Items on CT Dose with Use of Automated Tube Current Modulation-Pilot Investigation

PURPOSE

To determine the incidence and impact of overlying radiopaque personal items (e.g., cellular phones, zippers) on CT dose and image quality with use of automated tube current modulation.

METHODS

Topogram images from 100 consecutive adult outpatient CT abdomen pelvis studies were retrospectively reviewed, and the number and type of overlying radiopaque personal items were recorded. Additionally, an anthropomorphic phantom was imaged with overlying personal items 1) present in topogram and axial images; 2) present in topogram but removed prior to axial acquisition; and 3) present in topogram positioned outside the field of view of the axial acquisition. dose length product (DLP) and CT dose index volume (CTDIvol) were compared to acquisitions performed without overlying personal items. Image noise was evaluated by assessing the standard deviation of Hounsfield units at the level of the overlying personal item.

RESULTS

Overlying personal items were visible in topogram images for 55% of CT exams and included underwires (38% of exams), zippers (7%), and cellular phones (1%). DLP increased when a cellular phone was present in the topogram whether or not it was removed before axial image acquisition (3.7% p = 0.002, combined AutomA and SmartmA), and image noise increased (144%, p = 0.002; AutomA). No increase in dose or image noise was observed with overlying zippers or underwires or when any object was visible in the topogram outside the field of view of the axial images.

CONCLUSIONS

Overlying personal items were observed in the majority of abdominopelvic CT scans. Large overlying radiopaque personal items resulted in increased dose and increased image noise. Removal of all overlying personal items will result in optimized dose and image quality.

Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment

Background Nonalcoholic fatty liver disease and its consequences are a growing public health concern requiring cross-sectional imaging for noninvasive diagnosis and quantification of liver fat. Purpose To investigate a deep learning-based automated liver fat quantification tool at nonenhanced CT for establishing the prevalence of steatosis in a large screening cohort. Materials and Methods In this retrospective study, a fully automated liver segmentation algorithm was applied to noncontrast abdominal CT examinations from consecutive asymptomatic adults by using three-dimensional convolutional neural networks, including a subcohort with follow-up scans. Automated volume-based liver attenuation was analyzed, including conversion to CT fat fraction, and compared with manual measurement in a large subset of scans. Results A total of 11 669 CT scans in 9552 adults (mean age ± standard deviation, 57.2 years ± 7.9; 5314 women and 4238 men; median body mass index [BMI], 27.8 kg/m²) were evaluated, including 2117 follow-up scans in 1862 adults (mean age, 59.2 years; 971 women and 891 men; mean interval, 5.5 years). Algorithm failure occurred in seven scans. Mean CT liver attenuation was 55 HU ± 10, corresponding to CT fat fraction of 6.4% (slightly fattier in men than in women [7.4% ± 6.0 vs 5.8% ± 5.7%; P < .001]). Mean liver Hounsfield unit varied little by age (<4 HU difference among all age groups) and only weak correlation was seen with BMI (r² = 0.14). By category, 47.9% (5584 of 11 669) had negligible or no liver fat (CT fat fraction <5%), 42.4% (4948 of 11 669) had mild steatosis (CT fat fraction of 5%-14%), 8.8% (1025 of 11 669) had moderate steatosis (CT fat fraction of 14%-28%), and 1% (112 of 11 669) had severe steatosis (CT fat fraction >28%). Excellent agreement was seen between automated and manual measurements, with a mean difference of 2.7 HU (median, 3 HU) and r² of 0.92. Among the subcohort with longitudinal follow-up, mean change was only -3 HU ± 9, but 43.3% (806 of 1861) of patients changed steatosis category between first and last scans. Conclusion This fully automated CT-based liver fat quantification tool allows for population-based assessment of hepatic steatosis and nonalcoholic fatty liver disease, with objective data that match well with manual measurement. The prevalence of at least mild steatosis was greater than 50% in this asymptomatic screening cohort. © RSNA, 2019.

Automated segmentation and quantification of aortic calcification at abdominal CT: application of a deep learning-based algorithm to a longitudinal screening cohort

OBJECTIVE

To investigate an automated aortic calcium segmentation and scoring tool at abdominal CT in an adult screening cohort.

METHODS

Using instance segmentation with convolutional neural networks (Mask R-CNN), a fully automated vascular calcification algorithm was applied to a data set of 9914 non-contrast CT scans from 9032 consecutive asymptomatic adults (mean age, 57.5 ± 7.8 years; 4467 M/5447F) undergoing colonography screening. Follow-up scans were performed in a subset of 866 individuals (mean interval, 5.4 years). Automated abdominal aortic calcium volume, mass, and Agatston score were assessed. In addition, comparison was made with a separate validated semi-automated approach in a subset of 812 cases.

RESULTS

Mean values were significantly higher in males for Agatston score (924.2 ± 2066.2 vs. 564.2 ± 1484.2, p < 0.001), aortic calcium mass (222.2 ± 526.0 mg vs. 144.5 ± 405.4 mg, p < 0.001) and volume (699.4 ± 1552.4 ml vs. 426.9 ± 1115.5 HU, p < 0.001). Overall age-specific Agatston scores increased an average of 10%/year for the entire cohort; males had a larger Agatston score increase between the ages of 40 to 60 than females (91.2% vs. 75.1%, p < 0.001) and had significantly higher mean Agatston scores between ages 50 and 80 (p < 0.001). For the 812-scan subset with both automated and semi-automated methods, median difference in Agatston score was 66.4 with an r² agreement value of 0.84. Among the 866-patient cohort with longitudinal follow-up, the average Agatston score change was 524.1 ± 1317.5 (median 130.9), reflecting a mean increase of 25.5% (median 73.6%).

CONCLUSION

This robust, fully automated abdominal aortic calcification scoring tool allows for both individualized and population-based assessment. Such data could be automatically derived at non-contrast abdominal CT, regardless of the study indication, allowing for opportunistic assessment of cardiovascular risk.

Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment

OBJECTIVE

To investigate a fully automated abdominal CT-based muscle tool in a large adult screening population.

METHODS

A fully automated validated muscle segmentation algorithm was applied to 9310 non-contrast CT scans, including a primary screening cohort of 8037 consecutive asymptomatic adults (mean age, 57.1±7.8 years; 3555M/4482F). Sequential follow-up scans were available in a subset of 1171 individuals (mean interval, 5.1 years). Muscle tissue cross-sectional area and attenuation (Hounsfield unit, HU) at the L3 level were assessed, including change over time.

RESULTS

Mean values were significantly higher in males for both muscle area (190.6±33.6 vs 133.3±24.1 cm², p<0.001) and density (34.3±11.1 HU vs 27.3±11.7 HU, p<0.001). Age-related losses were observed, with mean muscle area reduction of -1.5 cm²/year and attenuation reduction of -1.5 HU/year. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes up to the age of 70 years. Between ages 50 and 70, relative muscle attenuation decreased significantly more in females (-30.6% vs -18.0%, p<0.001), whereas relative rates of muscle area loss were similar (-8%). Between ages 70 and 90, males lost more density (-22.4% vs -7.5%) and area (-13.4% vs -6.9%, p<0.001). Of the 1171 patients with longitudinal follow-up, 1013 (86.5%) showed a decrease in muscle attenuation, 739 (63.1%) showed a decrease in area, and 1119 (95.6%) showed a decrease in at least one of these measures.

CONCLUSION

This fully automated CT muscle tool allows for both individualized and population-based assessment. Such data could be automatically derived at abdominal CT regardless of study indication, allowing for opportunistic sarcopenia detection.

ADVANCES IN KNOWLEDGE

This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic sarcopenia assessment, regardless of the original clinical indication. Mean values were significantly higher in males for both muscle area and muscle density. Overall age-related muscle density (attenuation) loss was steeper than for muscle area for both sexes, and therefore may be a more valuable predictor of adverse outcomes.

Texture analysis of small renal cell carcinomas at MDCT for predicting relevant histologic and protein biomarkers

PURPOSE

To assess CT texture features of small renal cell carcinomas (≤ 4cm) for association with key pathologic features including protein biomarkers.

METHODS

Quantitative CT texture analysis (CTTA) of small renal cancers (≤ 4cm) was performed on non-contrast and portal venous phase abdominal MDCT scans with an ROI drawn at the largest cross-sectional diameter of the tumor using commercially available software. Texture parameters including mean pixel attenuation, the standard deviation (SD) of the pixel distribution histogram, entropy, the mean of positive pixels, the skewness (i.e., asymmetry) of the pixel histogram, kurtosis (i.e., peakness) of the pixel histogram, and the percentage of positive pixels were correlated with pathologic data from surgical resection, including histology and nuclear grade, as well as microarray analysis in a subset (n = 40) including Ki67 index, CRP, and neovascularization (CD105/CD31).

RESULTS

Portal venous phase images were available in 249 patients (105 women, 144 men; mean age, 56.7 years) with tumors ≤ 4cm (mean, median, range, ± SD; 2.66, 2.60, 0.3-4.0 ± 0.85 cm). CT texture features of standard deviation, mean of the positive pixels, and entropy of the pixel histogram were significantly associated with histologic cell type (clear vs. non-clear; p < 0.001). Entropy and mean of the positive pixels also showed an association with nuclear grade, although not statistically significant. In the microarray analysis subset, kurtosis of the pixel histogram was associated with CD105/CD31 (p = 0.05). SD also showed some association with CD 105 positivity (p = 0.02) and CAIX expression (p = 0.01). Non-contrast CT images were available in 174 patients (72 women, 102 men; mean age, 57.5 years). Although the association with histology was not as strong as on the portal venous phase, in the subset of patients with microarray data, SD was found to correlate with CRP (p = 0.08), kurtosis with CRP (p = 0.004), CD105/CD31 (p = 0.002), and with Ki 67 index (p < 0.001).

CONCLUSION

CT texture features were significantly associated with important histopathologic features in small renal cancers. These non-invasive measures can be performed retrospectively and may provide useful information when determining follow-up and treatment of small renal cancers.

Less barium enema, more colonoscopy: A 12-year nationwide population-based study in Taiwan

BACKGROUND

Colorectal cancer (CRC) is the second most common and third most fatal cancer in Taiwan. To reduce incidence and mortality rates from cancer, including CRC, the Health Promotion Administration in Taiwan initiated the National Program on Cancer Prevention in 2005. For patients who have a positive fecal occult blood test, colonoscopy is recommended, and double-contrast barium enema (BE) is reserved as an alternative for those who cannot receive colonoscopy. In addition, single-contrast BE is sometimes used in pediatrics to evaluate colonic condition. This study evaluated the usage trends of BE and colonoscopy in Taiwan.

METHODS

Data from the National Health Insurance Research Database from 2001 to 2013 were used in this study. Patients who received BE and colonoscopy were identified using the procedure codes of the National Health Insurance program. Age-standardized, yearly rates of BE and colonoscopy procedures were calculated.

RESULTS

According to the data, the total number of colonoscopies increased 3.7-fold from 2001 to 2013. The compound annual growth rates for BE and colonoscopy were -5.36% and 10.47%, respectively, during the same period. The compound annual growth rates for BE and colonoscopy were -3.89% and 11.64% from 2005 to 2009, and -11.36% and 9.82% from 2010 to 2013, respectively. BE was conducted significantly more frequently than colonoscopy in patients who were aged <12 years and in female patients.

CONCLUSION

Professional association guidelines, national cancer prevention programs, patient and physician preferences, and increasing awareness and knowledge of CRC may all contribute to the increasing use of colonoscopy and the dramatic decline in the use of BE in Taiwan.

Clinical Implementation of a Focused MRI Protocol for Hepatic Fat and Iron Quantification

OBJECTIVE. The purpose of this article is to describe our institutional experience with the clinical implementation of a novel focused rapid chemical shift-encoded MRI protocol specifically intended to detect and quantify hepatic steatosis and iron overload, highlighting usage statistics and issues related to cost. CONCLUSION. Focused MRI examinations for specific clinical indications, such as this protocol for detection and quantification of hepatic steatosis and iron overload, are feasible in a busy clinical practice and add value for patients and referring providers.

Multiparametric CT for Noninvasive Staging of Hepatitis C Virus-Related Liver Fibrosis: Correlation With the Histopathologic Fibrosis Score

OBJECTIVE

The objective was to develop a multiparametric CT algorithm to stage liver fibrosis in patients with chronic hepatitis C virus (HCV) infection.

MATERIALS AND METHODS

Abdominal CT and laboratory measures in 469 patients with HCV (340 men and 129 women; mean age, 50.1 years) were compared against the histopathologic Metavir fibrosis reference standard (F0, n = 49 patients; F1, n = 69 patients; F2, n = 102 patients; F3, n = 76 patients; F4, n = 173 patients). From the initial candidate pool, nine CT and two laboratory measures were included in the final assessment (CT-based features: hepatosplenic volumetrics, texture features, liver surface nodularity [LSN] score, and linear CT measurements; laboratory-based measures: Fibrosis-4 [FIB-4] score and aspartate transaminase-to-platelets ratio index [APRI]). Univariate logistic regression and multivariate logistic regression were performed with ROC analysis, proportional odds modeling, and probabilities.

RESULTS

ROC AUC values for the model combining all 11 parameters for discriminating significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (F4) were 0.928, 0.956, and 0.972, respectively. For all nine CT-based parameters, these values were 0.905, 0.936, and 0.972, respectively. Using more simplified panels of two, three, or four parameters yielded good diagnostic performance; for example, a two-parameter model combining only LSN score with FIB-4 score had ROC AUC values of 0.886, 0.915, and 0.932, for significant fibrosis, advanced fibrosis, and cirrhosis. The LSN score performed best in the univariate analysis.

CONCLUSION

Multiparametric CT assessment of HCV-related liver fibrosis further improves performance over the performance of individual parameters. An abbreviated panel of LSN score and FIB-4 score approached the diagnostic performance of more exhaustive panels. Results of the abbreviated panel compare favorably with elastography, but this approach has the advantage of retrospective assessment using preexisting data without planning.

Detection of Colorectal Hepatic Metastases Is Superior at Standard Radiation Dose CT versus Reduced Dose CT

Purpose To evaluate colorectal cancer hepatic metastasis detection and characterization between reduced radiation dose (RD) and standard dose (SD) contrast material-enhanced CT of the abdomen and to qualitatively compare between filtered back projection (FBP) and iterative reconstruction algorithms. Materials and Methods In this prospective study (from May 2017 through November 2017), 52 adults with biopsy-proven colorectal cancer and suspected hepatic metastases at baseline CT underwent two portal venous phase CT scans: SD and RD in the same breath hold. Three radiologists, blinded to examination details, performed detection and characterization of 2-15-mm lesions on the SD FBP and RD adaptive statistical iterative reconstruction (ASIR)-V 60% series images. Readers assessed overall image quality and lesions between SD FBP and seven different iterative reconstructions. Two nonblinded consensus reviewers established the reference standard using the picture archiving and communication system lesion marks of each reader, multiple comparison examinations, and clinical data. Results RD CT resulted in a mean dose reduction of 54% compared with SD. Of the 260 lesions (233 metastatic, 27 benign), 212 (82%; 95% confidence interval [CI]: 76%, 86%) were detected with RD CT, whereas 252 (97%; 95% CI: 94%, 99%) were detected with SD (P < .001); per-lesion sensitivity was 79% (95% CI: 74%, 84%) and 94% (95% CI: 90%, 96%) (P < .001), respectively. Mean qualitative scores ranked SD images as higher quality than RD series images, and ASIR-V ranked higher than ASIR and Veo 3.0. Conclusion CT evaluation of colorectal liver metastases is compromised with modest radiation dose reduction, and the use of iterative reconstructions could not maintain observer performance. © RSNA, 2018.

CT texture analysis of the liver for assessing hepatic fibrosis in patients with hepatitis C virus

OBJECTIVE

To evaluate CT texture analysis (CTTA) for non-invasively staging of hepatic fibrosis (stages F0-F4) in a cohort of patients with hepatitis C virus (HCV).

METHODS

Quantitative texture analysis of the liver was performed on abdominal multidimensional CT scans. Single slice region of interest measurements of the total liver, Couinaud segments IV-VIII and segments I-III were made. CT texture parameters were tested against stage of hepatic fibrosis in segments IV-VIII on the portal venous phase. Texture parameters were correlated with biopsy performed within 1 year for all cases with intermediate fibrosis (F0-F3).

RESULTS

CT scans of 556 adults (360 males, 196 females; mean age, 49.8 years), including a healthy control group (F0, n = 77) and patients with hepatitis C virus and Stage 0 disease (n = 49), and patients with increasing stages of fibrosis (F1, n = 80; F2 n = 99; F3 n = 87; F4 n = 164) were evaluated. Mean gray level intensity increased with increasing fibrosis. For significant fibrosis (≥F2), mean showed receiver operatingcharacteristic area under the curve (AUC) of 0.80 with sensitivity and specificity of 74 and 75% using a threshold of 0.44, with similar receiver operatingcharacteristic AUC and sensitivity/specificity for advanced fibrosis (≥F3). Skewness and kurtosis were inversely associated with hepatic fibrosis, most prominently in cirrhotic patients. A multivariate model combining these four texture features (mean, mpp, skewness and kurtosis) showed slightly improved performance with AUC of 0.82, 0.82 and 0.86 for any fibrosis (F0 vs F1-F4), significant fibrosis (F0-1 vs F2-4) and advanced fibrosis (F0-2 vs F3-4) respectively.

CONCLUSION

CT texture features may be associated with hepatic fibrosis and have utility in staging fibrosis, particularly at advanced levels.

ADVANCES IN KNOWLEDGE

CTTA may be helpful in detecting and staging hepatic fibrosis, particularly at advanced levels. CT measures like CTTA can be retrospectively evaluated without special equipment.

Opportunistic Screening for Hereditary Hemochromatosis With Unenhanced CT: Determination of an Optimal Liver Attenuation Threshold

OBJECTIVE

The purpose of this study was to assess whether a specific liver attenuation threshold for unenhanced CT allows both sensitive opportunistic detection of unsuspected hereditary hemochromatosis and low overall screening test-positive rates.

MATERIALS AND METHODS

We used a standard ROI placement method on unenhanced CT studies of 3357 consecutive adults (mean age, 57.0 years) with no symptoms of liver disease who underwent colorectal screening. Hepatic attenuation (in HU) was measured to assess test-positive rates at various liver attenuation thresholds. To assess sensitivity, unenhanced hepatic CT attenuation was also measured in 12 patients with hereditary hemochromatosis (mean age, 48.3 years), who were homozygous for the HFE C282Y mutation. All scans were obtained at 120 kV. Serum ferritin levels were recorded for the hereditary hemochromatosis cohort.

RESULTS

Mean liver attenuation ± SD among screened adults was 59.4 ± 12.7 HU, compared with 78.7 ± 13.1 HU (range, 59-105 HU) in the hereditary hemochromatosis cohort (p < 0.001). Screening test-positive rates were 30.6% (n = 1028) at 65 HU, 8.2% (n = 275) at 70 HU, 1.2% (n = 39) at 75 HU, and 0.2% (n = 7) at 80 HU. Corresponding sensitivities for hereditary hemochromatosis at these thresholds were 83.3% (10/12) at 65, 70, and 75 HU; and 50.0% (6/12) at 80 HU. Serum ferritin levels were elevated in all patients with hereditary hemochromatosis (mean, 1678 ng/mL; range, 477-3991 ng/mL).

CONCLUSION

An unenhanced CT liver attenuation threshold of 75 HU was sensitive (83.3%) for hereditary hemochromatosis while maintaining an acceptably low screening test-positive rate (1.2%). An unexplained liver attenuation of 75 HU or more on unenhanced CT should trigger appropriate laboratory investigation for iron overload; early intervention with phlebotomy can limit or prevent organ damage in patients with hemochromatosis.

Does Nonenhanced CT-based Quantification of Abdominal Aortic Calcification Outperform the Framingham Risk Score in Predicting Cardiovascular Events in Asymptomatic Adults?

Purpose To determine if abdominal aortic calcification (AAC) at CT predicts cardiovascular events independent of Framingham risk score (FRS). Materials and Methods For this retrospective study, electronic health records for 829 asymptomatic patients (mean age, 57.9 years; 451 women, 378 men) who underwent nonenhanced CT colonography screening between April 2004 and March 2005 were reviewed for subsequent cardiovascular events; mean follow-up interval was 11.2 years ± 2.8 (standard deviation). Institutional review board approval was obtained. CT-based AAC was retrospectively quantified as a modified Agatston score by using a semiautomated tool. Kaplan-Meier curves and Cox proportional hazards models were used for time-to-event analysis; receiver operating characteristic curves and net reclassification improvement compared predictive abilities of AAC and FRS. Results An index cardiovascular event occurred after CT in 156 (19%) of 829 patients (6.7 years ± 3.5, including heart attack in 39 [5%] and death in 79 [10%]). AAC was higher in the cardiovascular event cohort (mean AAC, 3478 vs 664; P < .001). AAC was a strong predictor of cardiovascular events at both univariable and multivariable Cox modeling, independent of FRS (P < .001). Kaplan-Meier plots showed better separation with AAC over FRS. The area under the receiver operating characteristic curve (AUC) was higher for AAC than FRS at all evaluated time points (eg, AUC of 0.82 vs 0.64 at 2 years; P = .014). By using a cutoff point of 200, AAC improved FRS risk categorization with net reclassification improvement of 35.4%. Conclusion CT-based abdominal aortic calcification was a strong predictor of future cardiovascular events, outperforming the Framingham risk score. This finding suggests a potential opportunistic role in abdominal nonenhanced CT scans performed for other clinical indications. © RSNA, 2018.

Characteristics of MR Neuroimaging Services Billed by Radiologists versus Nonradiologists

BACKGROUND AND PURPOSE

Although most neuroimaging examinations are interpreted by radiologists, many nonradiologists provide interpretation services. We studied day of the week, site of service, and patient complexity differences for common Medicare MR neuroimaging examinations interpreted by radiologists versus nonradiologists.

MATERIALS AND METHODS

Using carrier claims files for a 5% sample of Medicare beneficiaries from 2012 to 2014, we identified all claims for brain and lumbar spine MR imaging examinations. Services were categorized by physician specialty, day of the week, and the site of service. Patient complexity was calculated using Charlson Comorbidity Indices. The χ² was performed to test statistical significance.

RESULTS

A provider specialty could be identified for 568,423 brain and lumbar spine MR imaging examinations. Of weekday examinations, radiologists interpreted 475,288 (92.3%), and nonradiologists, 39,510 (7.7%). Of weekend examinations, radiologists interpreted 52,028 (97.0%) and nonradiologists 1597 (3.0%). Radiologists interpreted 145,904 (98.7%) examinations in the inpatient hospital and emergency department settings versus 1882 (1.3%) by nonradiologists. Of all examinations, 44,547 of those interpreted by radiologists (8.4%) were on the most clinically complex patients versus 2139 (5.2%) for nonradiologists. All interspecialty differences for day of the week, the site of service, and patient complexity were statistically significant (P < .001).

CONCLUSIONS

Although radiologists interpret most common MR neuroimaging examinations for Medicare beneficiaries, in contrast to nonradiologists, they disproportionately render those services on weekends, in higher acuity sites, and on more complex patients. To optimize access and minimize disparities in necessary neuroimaging, quality metrics should consider such service characteristics.

Multidetector Computed Tomography for Retrospective, Noninvasive Staging of Liver Fibrosis

Although not traditionally used to assess hepatic fibrosis, computed tomography (CT) is fast, accessible, robust, and commonly used for abdominal indications. CT metrics are often easily retrospectively obtained without special equipment. Metrics such as liver segmental volume ratio, which quantifies regional hepatic volume changes; splenic volume; and liver surface nodularity scoring show diagnostic performance comparable to elastography techniques for detecting significant and advanced fibrosis. Other emerging CT tools, such as CT texture analysis and fractional extracellular volume, have also shown promise in identifying fibrosis and warrant further study.

Imaging of the Postoperative Colon

Recognition of postoperative complications is important for the immediate diagnosis and treatment needed for appropriate patient care. Identification of postoperative complications from colon surgery requires not only knowledge of the type of procedure, but also the expected normal postoperative appearance. The purpose of this article is to discuss and review the expected anatomic changes after colorectal surgery, and the appearance of the most common postoperative complications.

Quantification of Liver Fat Content With Unenhanced MDCT: Phantom and Clinical Correlation With MRI Proton Density Fat Fraction

OBJECTIVE

The purpose of this study was to evaluate the relation between unenhanced CT liver attenuation values and MRI-derived proton density fat fraction (PDFF) for estimation of liver fat content at CT.

MATERIALS AND METHODS

A CT-MRI phantom was constructed and imaged containing 12 vials with lipid fractions ranging from 0% to 100%. For the retrospective clinical arm, 221 patients (120 men, 101 women; mean age, 54 years) underwent both unenhanced CT and chemical shift-encoded MRI of the liver between 2007 and 2017. Among these patients, 92 had more than one 120-kV CT scan for comparison. CT attenuation and MRI PDFF were derived with coregistered ROI measurements in the right hepatic lobe. The 120-kV subgroup of CT examinations performed within 1 month of MRI PDFF examinations (n = 72) served as the primary cohort for linear correlation. The effects of different tube voltage settings, time intervals between CT and MRI, and iron overload were assessed. Linear least squares regression analysis was performed.

RESULTS

Phantom results showed excellent linear fit between CT attenuation and MRI PDFF (r² = 0.986). In patients, 120-kV CT performed within 1 month of MRI PDFF exhibited strong linear correlation (r² = 0.828) that closely matched the phantom data, yielding the following clinical CT-MRI conversion formula: MRI PDFF (%) = -0.58 × CT attenuation (HU) + 38.2. Correlation worsened for CT-to-MRI intervals longer than 1 month (r² = 0.565), and this specific relationship did not apply as well to non-120-kV settings (r² = 0.554). For patients with multiple scans, correlation progressively worsened over time. CT-based liver fat content was underestimated in several patients with iron overload.

CONCLUSION

The linear correlation between unenhanced CT attenuation and MRI PDFF allows quantification of liver fat content by means of unenhanced CT in clinical practice. As expected, correlation worsened with increasing CT-MRI time interval, variable tube voltage settings, and iron overload.

Abdominal imaging ordering patterns by referring provider specialty

PURPOSE

Prior work has demonstrated marked growth in the volume of abdominal imaging performed by radiologists. However, decisions to pursue imaging are largely driven by referring providers. In this study, we take the novel approach of investigating abdominal imaging utilization patterns by referring provider specialty.

METHODS

Data on imaging services were obtained from the 2014 DocGraph Medicare Referring Provider Utilization for Procedures (MrPUP) public use file. MrPUP contains aggregated transaction data for combinations of unique referring provider and service code. Imaging services were classified by modality and body region using the Neiman Institute Types of Service (NITOS). Each referring provider's specialty was determined using Medicare Physician Compare. Abdominal imaging ordering patterns were summarized by referring specialty.

RESULTS

The final dataset included 5,824,754 abdominal imaging transactions. The most common ordering specialties of abdominal imaging were as follows: (1) internal medicine; (2) urology; (3) emergency medicine; (4) family practice; and (5) gastroenterology. The most common ordering specialties by abdominal imaging modality were emergency medicine for CT; gastroenterology for MRI and nuclear medicine; and internal medicine for ultrasound and radiography. While numerous specialties commonly ordered abdominal radiography and CT, urologists also commonly ordered retroperitoneal ultrasound and retrograde urography, and gastroenterologists also commonly ordered abdominal ultrasound, abdominal MRI, and esophagrams. Internal medicine, family practice, and emergency medicine providers ordered a much broader mix of imaging, including many non-abdominal imaging examinations.

CONCLUSION

Referring specialty abdominal imaging ordering patterns are varied but distinct. Awareness of these patterns may facilitate focused educational and policy initiatives to improve abdominal imaging appropriateness and utilization.