Diagnostic yield, safety, and outcomes of Head-to-pelvis sudden death CT imaging in post arrest care: The CT FIRST cohort study.

AIM: Our aim was to test whether a head-to-pelvis CT scan improves diagnostic yield and speed to identify causes for out of hospital circulatory arrest (OHCA). METHODS: CT FIRST was a prospective observational pre-/post-cohort study of patients successfully resuscitated from OHCA. Inclusion criteria included unknown cause for arrest, age >18 years, stability to undergo CT, and no known cardiomyopathy or obstructive coronary artery disease. A head-to-pelvis sudden death CT (SDCT) scan within 6 hours of hospital arrival was added to the standard of care for patients resuscitated from OHCA (post-cohort) and compared to standard of care (SOC) alone (pre-cohort). The primary outcome was SDCT diagnostic yield. Secondary outcomes included time to identifying OHCA cause and time-critical diagnoses, SDCT safety, and survival to hospital discharge. RESULTS: Baseline characteristics between the SDCT (N = 104) and the SOC (N = 143) cohorts were similar. CT scans (either head, chest, and/or abdomen) were ordered in 74 (52%) of SOC patients. Adding SDCT scanning identified 92% of causes for arrest compared to 75% (SOC-cohort; p value < 0.001) and reduced the time to diagnosis by 78% (SDCT 3.1 hours, SOC alone 14.1 hours, p < 0.0001). Identification of critical diagnoses was similar between cohorts, but SDCT reduced delayed (>6 hours) identification of critical diagnoses by 81% (p < 0.001). SDCT safety endpoints were similar including acute kidney injury. Patient survival to discharge was similar between cohorts. DISCUSSION: SDCT scanning early after OHCA resuscitation safely improved the efficiency and diagnostic yield for causes of arrest compared to the standard of care alone. CLINICAL TRIALS NUMBER: NCT03111043.

Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model.

Radiology reports contain a diverse and rich set of clinical abnormalities documented by radiologists during their interpretation of the images. Comprehensive semantic representations of radiological findings would enable a wide range of secondary use applications to support diagnosis, triage, outcomes prediction, and clinical research. In this paper, we present a new corpus of radiology reports annotated with clinical findings. Our annotation schema captures detailed representations of pathologic findings that are observable on imaging ("lesions") and other types of clinical problems ("medical problems"). The schema used an event-based representation to capture fine-grained details, including assertion, anatomy, characteristics, size, and count. Our gold standard corpus contained a total of 500 annotated computed tomography (CT) reports. We extracted triggers and argument entities using two state-of-the-art deep learning architectures, including BERT. We then predicted the linkages between trigger and argument entities (referred to as argument roles) using a BERT-based relation extraction model. We achieved the best extraction performance using a BERT model pre-trained on 3 million radiology reports from our institution: 90.9-93.4% F1 for finding triggers and 72.0-85.6% F1 for argument roles. To assess model generalizability, we used an external validation set randomly sampled from the MIMIC Chest X-ray (MIMIC-CXR) database. The extraction performance on this validation set was 95.6% for finding triggers and 79.1-89.7% for argument roles, demonstrating that the model generalized well to the cross-institutional data with a different imaging modality. We extracted the finding events from all the radiology reports in the MIMIC-CXR database and provided the extractions to the research community.

Impact of Follow-Up Imaging Recommendation Specificity on Adherence.

Radiology reports often contain follow-up imaging recommendations, but failure to comply with them in a timely manner can lead to delayed treatment, poor patient outcomes, complications, and legal liability. Using a dataset containing 2,972,164 exams for over 7 years, in this study we explored the association between recommendation specificity on follow-up rates. Our results suggest that explicitly mentioning the follow-up interval as part of a follow-up imaging recommendation has a significant impact on adherence making these recommendations 3 times more likely (95% CI: 2.95 - 3.05) to be followed-up, while explicit mentioning of the follow-up modality did not have a significant impact. Our findings can be incorporated into routine dictation macros so that the follow-up duration is explicitly mentioned whenever clinically applicable, and/or used as the basis for a quality improvement project focussed on improving adherence to follow-up imaging recommendations.

Correlating the Radiological Assessment of Patient Motion with the Incidence of Repeat Sequences Documented by Log Files.

OBJECTIVE: To correlate a radiological assessment of MR motion artifacts with the incidence of repeated sequences and delays derived from modality log files (MLFs) and investigate the suitability of log files for quantifying the operational impact of patient motion. MATERIALS AND METHODS: An experienced, blinded neuroradiologist retrospectively evaluated one full calendar month of sequentially obtained clinical MR exams of the head and/or brain for the presence of motion artifacts using a previously defined clinical grading scale. MLF data were analyzed to extract the occurrence of repeated sequences during the examinations. Statistical analysis included the determination of 95% confidence intervals for repetition ratios, and Welch's t-test to exclude the hypothesis of equal means for different groups of sequences. RESULTS: A total of 213 examinations were evaluated, comprising 1681 MLF-documented sequences, from which 1580 were archived. Radiological motion assessment scores (0, none to 4, severe) were assigned to each archived sequence. Higher motion scores correlated with a higher MLF-derived repetition probability, reflected by the average motion scores assigned to sequences that would be repeated (group 1, mean=2.5), those that are a repeat (group 2, mean=1.9), and those that are not repeated (group 3, mean=1.1) within an exam. The hypothesis of equal means was rejected with P = 5.9 × 10-5 for groups 1 and 2, P = 9.39 × 10-16 for groups 1 and 3, and P = 1.55 × 10-12 for groups 2 and 3. The repetition probability and associated time loss could be quantified for individual sequence types. The total time loss due to repeat sequence acquisition derived from MLFs was greater than four hours. CONCLUSION: Log file data may help assess patterns of scanner and exam performance and may be useful in identifying pitfalls to diagnostic imaging in a clinical environment, particularly with respect to patient motion.

Prevalence and Patterns of Resuscitation-Associated Injury Detected by Head-to-Pelvis Computed Tomography After Successful Out-of-Hospital Cardiac Arrest Resuscitation.

Background Patients resuscitated from out-of-hospital circulatory arrest (OHCA) frequently have cardiopulmonary resuscitation injuries identifiable by computed tomography, although the prevalence, types of injury, and effects on clinical outcomes are poorly characterized. Methods and Results We assessed the prevalence of resuscitation-associated injuries in a prospective, observational study of a head-to-pelvis sudden-death computed tomography scan within 6 hours of successful OHCA resuscitation. Primary outcomes included total injuries and time-critical injuries (such as organ laceration). Exploratory outcomes were injury associations with mechanical cardiopulmonary resuscitation and survival to discharge. Among 104 patients with OHCA (age 56±15 years, 30% women), 58% had bystander cardiopulmonary resuscitation, and total cardiopulmonary resuscitation time was 15±11 minutes. The prevalence of resuscitation-associated injury was high (81%), including 15 patients (14%) with time-critical findings. Patients with resuscitation injury were older (58±15 versus 46±13 years; P<0.001), but had otherwise similar baseline characteristics and survival compared with those without. Mechanical chest compression systems (27%) had more frequent sternal fractures (36% versus 12%; P=0.009), including displaced fractures (18% versus 1%; P=0.005), but no difference in survival (46% versus 41%; P=0.66). Conclusions In patients resuscitated from OHCA, head-to-pelvis sudden-death computed tomography identified resuscitation injuries in most patients, with nearly 1 in 7 with time-critical complications, and one-half with extensive rib-cage injuries. These data suggest that sudden-death computed tomography may have additional diagnostic utility and treatment implications beyond evaluating causes of OHCA. These important findings need to also be taken in context of the certain fatal outcome without resuscitation efforts. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03111043.

A Method for Reducing Variability Across Dual-Energy CT Manufacturers in Quantification of Low Iodine Content Levels.

BACKGROUND. Clinical use of the dual-energy CT (DECT) iodine quantification technique is hindered by between-platform (i.e., across different manufacturers) variability in iodine concentration (IC) values, particularly at low iodine levels. OBJECTIVE. The purpose of this study was to develop in an anthropomorphic phantom a method for reducing between-platform variability in quantification of low iodine content levels using DECT and to evaluate the method's performance in patients undergoing serial clinical DECT examinations on different platforms. METHODS. An anthropomorphic phantom in three body sizes, incorporating varied lesion types and scanning conditions, was imaged with three distinct DECT implementations from different manufacturers at varying radiation exposures. A cross-platform iodine quantification model for correcting between-platform variability at low iodine content was developed using the phantom data. The model was tested in a retrospective series of 30 patients (20 men, 10 women; median age, 62 years) who each underwent three serial contrast-enhanced DECT examinations of the abdomen and pelvis (90 scans total) for routine oncology surveillance using the same three DECT platforms as in the phantom. Estimated accuracy of phantom IC values was summarized using root-mean-square error (RMSE) relative to known IC. Between-platform variability in patients was summarized using root-mean-square deviation (RMSD). RMSE and RMSD were compared between platform-based IC (ICPB) and cross-platform IC (ICCP). ICPB was normalized to aorta and portal vein. RESULTS. In the phantom study, mean RMSE of ICPB across platforms and other experimental conditions was 0.65 ± 0.18 mg I/mL compared with 0.40 ± 0.08 mg I/mL for ICCP (38% decrease in mean RMSE; p < .05). Intrapatient between-platform variability across serial DECT examinations was higher for ICPB than ICCP (RMSD, 97% vs 88%; p < .001). Between-platform variability was not reduced by normalization of ICPB to aorta (RMSD, 97% vs 101%; p = .12) or portal vein (RMSD, 97% vs 97%; p = .81). CONCLUSION. The developed cross-platform method significantly decreased between-platform variability occurring at low iodine content with platform-based DECT iodine quantification. CLINICAL IMPACT. With further validation, the cross-platform method, which has been implemented as a web-based app, may expand clinical use of DECT iodine quantification, yielding meaningful IC values that reflect tissue biologic viability or treatment response in patients who undergo serial examinations on different platforms.

Management of gastrointestinal bleeding: Society of Abdominal Radiology (SAR) Institutional Survey.

Despite guidelines developed to standardize the diagnosis and management of gastrointestinal (GI) bleeding, significant variability remains in recommendations and practice. The purpose of this survey was to obtain information on practice patterns for the evaluation of overt lower GI bleeding (LGIB) and suspected small bowel bleeding. A 34-question electronic survey was sent to all Society of Abdominal Radiology (SAR) members. Responses were received from 52 unique institutions (40 from the United States). Only 26 (50%) utilize LGIB management guidelines. 32 (62%) use CT angiography (CTA) for initial evaluation in unstable patients. In stable patients with suspected LGIB, CTA is the preferred initial exam at 21 (40%) versus colonoscopy at 24 (46%) institutions. CTA use increases after hours for both unstable (n = 32 vs. 35, 62% vs. 67%) and stable patients (n = 21 vs. 27, 40% vs 52%). CTA is required before conventional angiography for stable (n = 36, 69%) and unstable (n = 15, 29%) patients. 38 (73%) institutions obtain two post-contrast phases for CTA. 49 (94%) institutions perform CT enterography (CTE) for occult small bowel bleeding with capsule endoscopy (n = 26, 50%) and CTE (n = 21, 40%) being the initial test performed. 35 (67%) institutions perform multiphase CTE for occult small bowel bleeding. In summary, stable and unstable patients with overt lower GI are frequently imaged with CTA, while CTE is frequently performed for suspected occult small bowel bleeding.

Gastrointestinal Bleeding at CT Angiography and CT Enterography: Imaging Atlas and Glossary of Terms.

Gastrointestinal (GI) bleeding is a common potentially life-threatening medical condition frequently requiring multidisciplinary collaboration to reach the proper diagnosis and guide management. GI bleeding can be overt (eg, visible hemorrhage such as hematemesis, hematochezia, or melena) or occult (eg, positive fecal occult blood test or iron deficiency anemia). Upper GI bleeding, which originates proximal to the ligament of Treitz, is more common than lower GI bleeding, which arises distal to the ligament of Treitz. Small bowel bleeding accounts for 5-10% of GI bleeding cases commonly manifesting as obscure GI bleeding, where the source remains unknown after complete GI tract endoscopic and imaging evaluation. CT can aid in identifying the location and cause of bleeding and is an important complementary tool to endoscopy, nuclear medicine, and angiography in evaluating patients with GI bleeding. For radiologists, interpreting CT scans in patients with GI bleeding can be challenging owing to the large number of images and the diverse potential causes of bleeding. The purpose of this pictorial review by the Society of Abdominal Radiology GI Bleeding Disease-Focused Panel is to provide a practical resource for radiologists interpreting GI bleeding CT studies that reviews the proper GI bleeding terminology, the most common causes of GI bleeding, key patient history and risk factors, the optimal CT imaging technique, and guidelines for case interpretation and illustrates many common causes of GI bleeding. A CT reporting template is included to help generate radiology reports that can add value to patient care. An invited commentary by Al Hawary is available online. Online supplemental material is available for this article. ©RSNA, 2021.

Determining Follow-Up Imaging Study Using Radiology Reports.

Radiology reports often contain follow-up imaging recommendations. Failure to comply with these recommendations in a timely manner can lead to delayed treatment, poor patient outcomes, complications, unnecessary testing, lost revenue, and legal liability. The objective of this study was to develop a scalable approach to automatically identify the completion of a follow-up imaging study recommended by a radiologist in a preceding report. We selected imaging-reports containing 559 follow-up imaging recommendations and all subsequent reports from a multi-hospital academic practice. Three radiologists identified appropriate follow-up examinations among the subsequent reports for the same patient, if any, to establish a ground-truth dataset. We then trained an Extremely Randomized Trees that uses recommendation attributes, study meta-data and text similarity of the radiology reports to determine the most likely follow-up examination for a preceding recommendation. Pairwise inter-annotator F-score ranged from 0.853 to 0.868; the corresponding F-score of the classifier in identifying follow-up exams was 0.807. Our study describes a methodology to automatically determine the most likely follow-up exam after a follow-up imaging recommendation. The accuracy of the algorithm suggests that automated methods can be integrated into a follow-up management application to improve adherence to follow-up imaging recommendations. Radiology administrators could use such a system to monitor follow-up compliance rates and proactively send reminders to primary care providers and/or patients to improve adherence.

Society of abdominal radiology gastrointestinal bleeding disease-focused panel consensus recommendations for CTA technical parameters in the evaluation of acute overt gastrointestinal bleeding.

PURPOSE: To formulate consensus recommendations for CT angiography technical parameters used to evaluate overt gastrointestinal (GI) bleeding. METHODS: An electronic questionnaire consisting of 17 questions was sent to a panel of 16 radiologists with expertise on the imaging of GI bleeding from the Society of Abdominal Radiology GI Bleeding disease-focused panel to obtain consensus agreement on issues related to CTA technical parameters for imaging overt GI bleeding. A multi-round Delphi method of voting was performed to obtain consensus which was defined as ≥ 80% agreement. RESULTS: Consensus agreement was reached in 15/17 (89%) of the questions including the technique for the administration of IV contrast, the number of phases, scan timing, and image reconstruction. CONCLUSIONS: A panel of experts on the imaging of GI bleeding from the Society of Abdominal Radiology was able to reach consensus on the majority of technical parameters used for CTA of overt GI bleeding. These recommendations should improve the quality of patient care by adopting these minimal technical requirements for optimal exam performance and lead to less variation in the performance of these exams which will facilitate collecting and comparing published data from different centers. These recommendations will need revisions as additional scientific data become available.

Clinical and Payer-Based Analysis of Value of Dual-Energy Computed Tomography for Workup of Incidental Abdominal Findings.

OBJECTIVE: To perform a clinical and payer-based analysis of the value of dual-energy computed tomography (DECT) for workup of incidental abdominal findings. METHODS: This was a single-center, retrospectively designed, Health Insurance Portability and Accountability Act-compliant study approved by our institutional review board. Sixty-nine examinations in 69 patients (45 men, 24 women; mean age, 57.7 years) who underwent single-phase postcontrast abdominal DECT studies between January 1, 2011, and December 31, 2017, were included. Two radiologists, blinded to study objective and design, reviewed all cases and identified incidental abdominal findings needing further imaging. All incidental findings were reviewed by 2 other investigators, who determined whether an imaging-based diagnosis could be made using DECT virtual noncontrast images and iodine maps. Additional studies and associated payer-reimbursement amounts avoided by use of DECT were estimated. All imaging costs were estimated based on the US Centers for Medicare & Medicaid Services reimbursement amounts. RESULTS: Thirty-four incidental findings (renal mass, n = 20; adrenal nodule, n = 8; pancreatic cystic lesions, n = 3; others, n = 3) were identified in 19 (27.5%) of 69 patients. Dual-energy computed tomography characterized 27 incidental findings in 15 patients and accounted for cost savings of 15 additional imaging examinations (abdominal magnetic resonance imaging, n = 11; abdominal computed tomography, n = 4). Based on Centers for Medicare & Medicaid Services reimbursement amounts, we estimated that, by abolishing the need for additional imaging use, DECT saved US $84.95 per patient. CONCLUSIONS: Dual-energy computed tomography can provide an imaging-based diagnosis of incidental abdominal findings, otherwise incompletely characterized on routine abdominal computed tomography, in approximately 21% of patients. In select patients, the monetary savings from abolishing additional imaging may reduce payer costs associated with use of DECT.

Environmental Factors Predictive of No-Show Visits in Radiology: Observations of Three Million Outpatient Imaging Visits Over 16 Years.

PURPOSE: To evaluate the impact of environmental and socioeconomic factors on outpatient cancellations and "no-show visits" (NSVs) in radiology. MATERIALS AND METHODS: We conducted a retrospective analysis by collecting environmental factor data related to outpatient radiology visits occurring between 2000 and 2015 at our multihospital academic institution. Appointment attendance records were joined with daily weather observations from the National Oceanic and Atmospheric Administration and estimated median income from the US Census American Community Survey. A multivariate logistic regression model was built to examine relationships between NSV rate and median income, commute distance, maximum daily temperature, and daily snowfall. RESULTS: There were 270,574 (8.0%) cancellations and 87,407 (2.6%) NSVs among 3,379,947 scheduled outpatient radiology appointments and 575,206 unique patients from 2000 to 2015. Overall cancellation rates decreased from 14% to 8%, and NSV rates decreased from 6% to 1% as median income increased from $20,000 to $120,000 per year. In a multivariate model, the odds of NSV decreased 10.7% per $10,000 increase in median income (95% confidence interval [CI]: 10.3%-11.1%) and 2.0% per 10°F increase in maximum daily temperature (95% CI: 1.3%-1.6%). The odds of NSV increased 1.4% per 10-mile increase in commute distance (95% CI: 1.3%-1.6%) and 4.5% per 1-inch increase in daily snowfall (95% CI: 3.6%-5.3%). Commute distance was more strongly associated with NSV for those in the two lower tertiles of income than the highest tertile (P < .001). CONCLUSION: Environmental factors are strongly associated with patients' attendance at scheduled outpatient radiology examinations. Modeling of appointment failure risk based on environmental features can help increase the attendance of outpatient radiology appointments.

Automated Tracking of Follow-Up Imaging Recommendations.

OBJECTIVE. Radiology reports often contain follow-up imaging recommendations. Failure to comply with these recommendations in a timely manner can lead to poor patient outcomes, complications, and legal liability. As such, the primary objective of this research was to determine adherence rates to follow-up recommendations. MATERIALS AND METHODS. Radiology-related examination data, including report text, for examinations performed between June 1, 2015, and July 31, 2017, were extracted from the radiology departments at the University of Washington (UW) and Lahey Hospital and Medical Center (LHMC). The UW dataset contained 923,885 examinations, and the LHMC dataset contained 763,059 examinations. A 1-year period was used for detection of imaging recommendations and up to 14-months for the follow-up examination to be performed. RESULTS. On the basis of an algorithm with 97.9% detection accuracy, the follow-up imaging recommendation rate was 11.4% at UW and 20.9% at LHMC. Excluding mammography examinations, the overall follow-up imaging adherence rate was 51.9% at UW (range, 44.4% for nuclear medicine to 63.0% for MRI) and 52.0% at LHMC (range, 30.1% for fluoroscopy to 63.2% for ultrasound) using a matcher algorithm with 76.5% accuracy. CONCLUSION. This study suggests that follow-up imaging adherence rates vary by modality and between sites. Adherence rates can be influenced by various legitimate factors. Having the capability to identify patients who can benefit from patient engagement initiatives is important to improve overall adherence rates. Monitoring of follow-up adherence rates over time and critical evaluation of variation in recommendation patterns across the practice can inform measures to standardize and help mitigate risk.

Automatic Normalization of Anatomical Phrases in Radiology Reports Using Unsupervised Learning.

In today's radiology workflow, free-text reporting is established as the most common medium to capture, store, and communicate clinical information. Radiologists routinely refer to prior radiology reports of a patient to recall critical information for new diagnosis, which is quite tedious, time consuming, and prone to human error. Automatic structuring of report content is desired to facilitate such inquiry of information. In this work, we propose an unsupervised machine learning approach to automatically structure radiology reports by detecting and normalizing anatomical phrases based on the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) ontology. The proposed approach combines word embedding-based semantic learning with ontology-based concept mapping to derive the desired concept normalization. The word embedding model was trained using a large corpus of unlabeled radiology reports. Fifty-six anatomical labels were extracted from SNOMED CT as class labels of the whole human anatomy. The proposed framework was compared against a number of state-of-the-art supervised and unsupervised approaches. Radiology reports from three different clinical sites were manually labeled for testing. The proposed approach outperformed other techniques yielding an average precision of 82.6%. The proposed framework boosts the coverage and performance of conventional approaches for concept normalization, by applying word embedding techniques in semantic learning, while avoiding the challenge of having access to a large amount of annotated data, which is typically required for training classifiers.

Diagnostic yield of non-invasive imaging in patients following non-traumatic out-of-hospital sudden cardiac arrest: A systematic review.

AIM: To review data for non-invasive imaging in the diagnosis of non-traumatic out-of-hospital cardiac arrest (OHCA). DATA SOURCES: We searched MEDLINE, EMBASE, Cochrane library, and clinicaltrials.gov databases from inception to January 2017 for studies utilizing non-invasive imaging to identify potential causes of OHCA [computed tomography (CT), ultrasound including echocardiography, and magnetic resonance (MRI)]. STUDY SELECTION: Inclusion criteria were the following: (1) randomized control trials, cohort studies or observational studies; (2) contained a population ≥18 years old with non-traumatic OHCA who underwent diagnostic imaging with CT, MRI, echocardiography, or abdominal ultrasound; (3) imaging was obtained for diagnostic purposes; (4) patients were alive or were undergoing cardiopulmonary resuscitation at the time of imaging; (5) contained potential causes of OHCA. Endpoints studied were the number of potential OHCA causes identified, diagnostic accuracy measures (sensitivity, specificity, positive and negative predictive values), and diagnostic utility (number of imaging findings with reported changes in clinical management). RESULTS: Of the total 5722 studies identified, 17 (0.3%) met inclusion criteria. The majority of studies assessed the utility of CT in OHCA (n=10), and potential causes of OHCA were found in 8-54% of patients following head, abdominal and/or chest CT. Only 1/17 (6%) studies reported diagnostic accuracy measures, and 9/17 (53%) studies included a time to imaging criteria within 24h. CONCLUSION: Although non-invasive imaging is commonly performed in patients after OHCA, its diagnostic utility remains poorly characterized. Prospective studies are needed for appropriate imaging selection and their potential impact on treatment and outcome.

Repeat CT Performed Within One Month of CT Conducted in the Emergency Department for Abdominal Pain: A Secondary Analysis of Data From a Prospective Multicenter Study.

OBJECTIVE: The purpose of this study is to determine both the frequency of repeat CT performed within 1 month after a patient visits the emergency department (ED) and undergoes CT evaluation for abdominal pain and the frequency of worsened or new CT-based diagnoses. SUBJECTS AND METHODS: Secondary analysis was performed on data collected during a prospective multicenter study. The parent study included patients who underwent CT in the ED for abdominal pain between 2012 and 2014, and these patients constituted the study group of the present analysis. The proportion of patients who underwent (in any setting) repeat abdominal CT within 1 month of the index CT examination was calculated. For each of these patients, results of the index and repeat CT scans were compared by an independent panel and categorized as follows: no change (group 1); same process, improved (group 2); same process, worse (group 3); or different process (group 4). The proportion of patients in groups 1 and 2 versus groups 3 and 4 was calculated, and patient and ED physician characteristics were compared. RESULTS: The parent study included 544 patients (246 of whom were men [45%]; mean patient age, 49.4 years). Of those 544 patients, 53 (10%; 95% CI, 7.5-13%) underwent repeat abdominal CT. Patients' CT comparisons were categorized as follows: group 1 for 43% of patients (23/53), group 2 for 26% (14/53), group 3 for 15% (8/53), and group 4 for 15% (8/53). New or worse findings were present in 30% of patients (16/53) (95% CI, 19-44%). When patients with findings in groups 1 and 2 were compared to patients with findings in groups 3 and 4, no significant difference was noted in patient age (p = 0.25) or sex (p = 0.76), the number of days between scans (p = 0.98), and the diagnostic confidence of the ED physician after the index CT scan was obtained (p = 0.33). CONCLUSION: Short-term, repeat abdominal CT was performed for 10% of patients who underwent CT in the ED for abdominal pain, and it yielded new or worse findings for 30% of those patients.

Pericardial rupture and cardiac herniation in blunt trauma.

Pericardial rupture in blunt trauma is rarely seen on computed tomography (CT) imaging due to its high initial mortality. We report a case of a 53-year-old man who presented to the Emergency Department in hemodynamic shock after intentional fall from height. Chest radiograph, which was taken in the trauma bay as a part of his primary survey, showed abnormal mediastinum contour with pneumopericardium. Pericardial rupture with cardiac herniation, and tamponade secondary to pneumopericardium, was diagnosed on trauma CT scan. The patient underwent emergent surgical management with thoracotomy to reduce the herniation and repair the pericardium. Immediate suspicion for pericardial and cardiac injury on the initial chest radiograph and rapid diagnosis on CT was indispensable for this patient's favorable outcome.

CT Detectability of Small Low-Contrast Hypoattenuating Focal Lesions: Iterative Reconstructions versus Filtered Back Projection.

Purpose To investigate performance in detectability of small (≤1 cm) low-contrast hypoattenuating focal lesions by using filtered back projection (FBP) and iterative reconstruction (IR) algorithms from two major CT vendors across a range of 11 radiation exposures. Materials and Methods A low-contrast detectability phantom consisting of 21 low-contrast hypoattenuating focal objects (seven sizes between 2.4 and 10.0 mm, three contrast levels) embedded into a liver-equivalent background was scanned at 11 radiation exposures (volume CT dose index range, 0.5-18.0 mGy; size-specific dose estimate [SSDE] range, 0.8-30.6 mGy) with four high-end CT platforms. Data sets were reconstructed by using FBP and varied strengths of image-based, model-based, and hybrid IRs. Sixteen observers evaluated all data sets for lesion detectability by using a two-alternative-forced-choice (2AFC) paradigm. Diagnostic performances were evaluated by calculating area under the receiver operating characteristic curve (AUC) and by performing noninferiority analyses. Results At benchmark exposure, FBP yielded a mean AUC of 0.79 ± 0.09 (standard deviation) across all platforms which, on average, was approximately 2% lower than that observed with the different IR algorithms, which showed an average AUC of 0.81 ± 0.09 (P = .12). Radiation decreases of 30%, 50%, and 80% resulted in similar declines of observer detectability with FBP (mean AUC decrease, -0.02 ± 0.05, -0.03 ± 0.05, and -0.05 ± 0.05, respectively) and all IR methods investigated (mean AUC decrease, -0.00 ± 0.05, -0.04 ± 0.05, and -0.04 ± 0.05, respectively). For each radiation level and CT platform, variance in performance across observers was greater than that across reconstruction algorithms (P = .03). Conclusion Iterative reconstruction algorithms have limited radiation optimization potential in detectability of small low-contrast hypoattenuating focal lesions. This task may be further complicated by a high degree of variation in radiologists' performances, seemingly exceeding real performance differences among reconstruction algorithms. © RSNA, 2018 Online supplemental material is available for this article.

Understanding Why Patients No-Show: Observations of 2.9 Million Outpatient Imaging Visits Over 16 Years.

PURPOSE: To understand why patients "no-show" for imaging appointments, and to provide new insights for improving resource utilization. MATERIALS AND METHODS: We conducted a retrospective analysis of nearly 2.9 million outpatient examinations in our radiology information system from 2000 to 2015 at our multihospital academic institution. No-show visits were identified by the "reason code" entry "NOSHOW" in our radiology information system. We restricted data to radiography, CT, mammography, MRI, ultrasound, and nuclear medicine examinations that included all studied variables. These variables included modality, patient age, appointment time, day of week, and scheduling lead time. Multivariate logistic regression was used to identify factors associated with no-show visits. RESULTS: Out of 2,893,626 patient visits that met our inclusion criteria, there were 94,096 no-shows during the 16-year period. Rates of no-show visits varied from 3.36% in 2000 to 2.26% in 2015. The effect size for no-shows was strongest for modality and scheduling lead time. Mammography had the highest modality no-show visit rate of 6.99% (odds ratio [OR] 5.38, P < .001) compared with the lowest modality rate of 1.25% in radiography. Scheduling lead time greater than 6 months was associated with more no-show visits than scheduling within 1 week (OR 3.18, P < .001). Patients 60 years and older were less likely to miss imaging appointments than patients under 40 (OR 0.70, P < .001). Mondays and Saturdays had significantly higher rates of no-show than Sundays (OR 1.52 and 1.51, P < .001). CONCLUSION: Modality type and scheduling lead time were the most predictive factors of no-show. This may be used to guide new interventions such as targeted reminders and flexible scheduling.