Radiologists predict differential resource utilization but not clinical outcome in emergency department patients imaged with ultrasound for right upper quadrant pain.

PURPOSE: Radiologists with diverse training, specialization, and habits interpret imaging in the Emergency Department. It is necessary to understand if their variation predicts differential value. The purpose of this study was to determine whether attending radiologist variation predicts major clinical outcomes in adult Emergency Department patients imaged with ultrasound for right upper quadrant pain. METHODS: Consecutive ED patients imaged with ultrasound for RUQ pain from 10/8/2016 to 8/10/2022 were included (N = 7097). The primary outcome was prediction of hospital admission by signing attending radiologist. Secondary outcomes included: ED and hospital length of stay (LOS), 30-day mortality, 30-day re-presentation rate, subspecialty consultation, advanced imaging follow up (HIDA, MRI, CT), and intervention (ERCP, drainage or surgery). Sample size was determined a priori (detectable effect size: w = 0.06). Data were adjusted for demographic data, Elixhauser comorbidities, number of ED visits in prior year, clinical data, and system factors (38 covariates). P-values were corrected for multiple comparisons (false discovery rate-adjusted p-values). RESULTS: The included ultrasounds were read by 35 radiologists (median exams/radiologist: 145 [74.5-241.5]). Signing radiologist did not predict hospitalization (p = 0.85), abdominopelvic surgery or intervention within 30 days, re-presentation to the Emergency Department within 30 days, or subspecialty consultation. Radiologist did predict difference in Emergency Department length of stay (p < 0.001) although this difference was small and imprecise. HIDA was mentioned variably by radiologists (range 0-19%, p < 0.001), and mention of HIDA in the ultrasound report increased 10-fold the odds of HIDA being performed in the next 72 h (odds ratio 10.4 [8.0-13.4], p < 0.001). CONCLUSION: Radiologist variability did not predict meaningful outcome differences for patients with right upper quadrant pain undergoing ultrasound in the Emergency Department, but when radiologists mention HIDA in their reports, it predicts a 10-fold increase in the odds a HIDA is performed. Radiologists are relied on for interpretation that shapes subsequent patient care, and it is important to consider how radiologist variability can influence both outcome and resource utilization.

Diagnostic yield of whole-body 18F-FDG PET/CT in patients with suspected cardiac sarcoidosis.

BACKGROUND: Whole-body F-18 FDG PET has been included in the 2014 Heart Rhythm Society guidelines for cardiac sarcoidosis evaluation to identify alternate sites of biopsy prior to endomyocardial biopsy. The purpose of this study was to evaluate the diagnostic yield of whole-body F-18 FDG PET/CT. METHODS: All adult patients with suspected cardiac sarcoidosis undergoing same-day cardiac F-18 FDG PET/CT and whole-body F-18 FDG PET/CT between 10/1/2016 and 6/14/2021 to assess potential biopsy sites were retrospectively identified. Clinical indications, findings, recommendations, and outcomes were assessed. RESULTS: Eighty-eight patients were included. Extracardiac PET findings suggestive of sarcoidosis were present in 30 patients (34%), 27 of which had thoracic findings (90%). Sarcoidosis was diagnosed in 11% of patients. Only 1% (1/88) was diagnosed by extrathoracic biopsy of a whole-body PET finding. Incidental findings were common (31%), resulting in 11 additional tests or interventions. Recommendations from extrathoracic findings affected treatment in one case: a drainage catheter placement into an unsuspected pelvic abscess. CONCLUSION: Addition of whole-body F-18 FDG PET/CT to cardiac F-18 FDG PET/CT for the identification of extrathoracic sites of biopsy in patients with suspected cardiac sarcoidosis has marginal diagnostic yield but commonly results in incidental findings that rarely affect patient outcome.

Intra- and inter-operator variability in MRI-based manual segmentation of HCC lesions and its impact on dosimetry.

PURPOSE: The aim was to quantify inter- and intra-observer variability in manually delineated hepatocellular carcinoma (HCC) lesion contours and the resulting impact on radioembolization (RE) dosimetry. METHODS: Ten patients with HCC lesions treated with Y-90 RE and imaged with post-therapy Y-90 PET/CT were selected for retrospective analysis. Three radiologists contoured 20 lesions manually on baseline multiphase contrast-enhanced MRIs, and two of the radiologists re-contoured at two additional sessions. Contours were transferred to co-registered PET/CT-based Y-90 dose maps. Volume-dependent recovery coefficients were applied for partial volume correction (PVC) when reporting mean absorbed dose. To understand how uncertainty varies with tumor size, we fit power models regressing relative uncertainty in volume and in mean absorbed dose on contour volume. Finally, we determined effects of segmentation uncertainty on tumor control probability (TCP), as calculated using logistic models developed in a previous RE study. RESULTS: The average lesion volume ranged from 1.8 to 194.5 mL, and the mean absorbed dose ranged from 23.4 to 1629.0 Gy. The mean inter-observer Dice coefficient for lesion contours was significantly less than the mean intra-observer Dice coefficient (0.79 vs. 0.85, p < 0.001). Uncertainty in segmented volume, as measured by the Coefficient of Variation (CV), ranged from 4.2 to 34.7% with an average of 17.2%. The CV in mean absorbed dose had an average value of 5.4% (range 1.2-13.1%) without PVC while it was 15.1% (range 1.5-55.2%) with PVC. Using the fitted models for uncertainty as a function of volume on our prior data, the mean change in TCP due to segmentation uncertainty alone was estimated as 16.2% (maximum 48.5%). CONCLUSIONS: Though we find relatively high inter- and intra-observer reliability overall, uncertainty in tumor contouring propagates into non-negligible uncertainty in dose metrics and outcome prediction for individual cases that should be considered in dosimetry-guided treatment.

Computerized Decision Support for Bladder Cancer Treatment Response Assessment in CT Urography: Effect on Diagnostic Accuracy in Multi-Institution Multi-Specialty Study.

This observer study investigates the effect of computerized artificial intelligence (AI)-based decision support system (CDSS-T) on physicians' diagnostic accuracy in assessing bladder cancer treatment response. The performance of 17 observers was evaluated when assessing bladder cancer treatment response without and with CDSS-T using pre- and post-chemotherapy CTU scans in 123 patients having 157 pre- and post-treatment cancer pairs. The impact of cancer case difficulty, observers' clinical experience, institution affiliation, specialty, and the assessment times on the observers' diagnostic performance with and without using CDSS-T were analyzed. It was found that the average performance of the 17 observers was significantly improved (p = 0.002) when aided by the CDSS-T. The cancer case difficulty, institution affiliation, specialty, and the assessment times influenced the observers' performance without CDSS-T. The AI-based decision support system has the potential to improve the diagnostic accuracy in assessing bladder cancer treatment response and result in more consistent performance among all physicians.

Multicenter Evaluation of Multiparametric MRI Clear Cell Likelihood Scores in Solid Indeterminate Small Renal Masses.

Background Solid small renal masses (SRMs) (≤4 cm) represent benign and malignant tumors. Among SRMs, clear cell renal cell carcinoma (ccRCC) is frequently aggressive. When compared with invasive percutaneous biopsies, the objective of the proposed clear cell likelihood score (ccLS) is to classify ccRCC noninvasively by using multiparametric MRI, but it lacks external validation. Purpose To evaluate the performance of and interobserver agreement for ccLS to diagnose ccRCC among solid SRMs. Materials and Methods This retrospective multicenter cross-sectional study included patients with consecutive solid (≥25% approximate volume enhancement) SRMs undergoing multiparametric MRI between December 2012 and December 2019 at five academic medical centers with histologic confirmation of diagnosis. Masses with macroscopic fat were excluded. After a 1.5-hour training session, two abdominal radiologists per center independently rendered a ccLS for 50 masses. The diagnostic performance for ccRCC was calculated using random-effects logistic regression modeling. The distribution of ccRCC by ccLS was tabulated. Interobserver agreement for ccLS was evaluated with the Fleiss κ statistic. Results A total of 241 patients (mean age, 60 years ± 13 [SD]; 174 men) with 250 solid SRMs were evaluated. The mean size was 25 mm ± 8 (range, 10-39 mm). Of the 250 SRMs, 119 (48%) were ccRCC. The sensitivity, specificity, and positive predictive value for the diagnosis of ccRCC when ccLS was 4 or higher were 75% (95% CI: 68, 81), 78% (72, 84), and 76% (69, 81), respectively. The negative predictive value of a ccLS of 2 or lower was 88% (95% CI: 81, 93). The percentages of ccRCC according to the ccLS were 6% (range, 0%-18%), 38% (range, 0%-100%), 32% (range, 60%-83%), 72% (range, 40%-88%), and 81% (range, 73%-100%) for ccLSs of 1-5, respectively. The mean interobserver agreement was moderate (κ = 0.58; 95% CI: 0.42, 0.75). Conclusion The clear cell likelihood score applied to multiparametric MRI had moderate interobserver agreement and differentiated clear cell renal cell carcinoma from other solid renal masses, with a negative predictive value of 88%. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Mileto and Potretzke in this issue.

Interrater Agreement of Bosniak Classification Version 2019 and Version 2005 for Cystic Renal Masses at CT and MRI.

Background The Bosniak classification system for cystic renal masses was updated in 2019 in part to improve agreement compared with the 2005 version. Purpose To compare and investigate interrater agreement of Bosniak version 2019 and Bosniak version 2005 at CT and MRI. Materials and Methods In this retrospective single-center study, a blinded eight-reader assessment was performed in which 195 renal masses prospectively considered Bosniak IIF-IV (95 at CT, 100 at MRI, from 2006 to 2019 with version 2005) were re-evaluated with Bosniak versions 2019 and 2005. Radiologists (four faculty members, four residents) who were blinded to the initial clinical reading and histopathologic findings assessed all feature components and reported the overall Bosniak class for each system independently. Agreement was assessed with Gwet agreement coefficients. Uni- and multivariable linear regression models were developed to identify predictors of dispersion in the final Bosniak class assignment that could inform system refinement. Results A total of 185 patients were included (mean age, 63 years ± 13 [standard deviation]; 118 men). Overall interrater agreement was similar between Bosniak version 2019 and version 2005 (Gwet agreement coefficient: 0.51 [95% CI: 0.45, 0.57] vs 0.46 [95% CI: 0.42, 0.51]). This was true for experts (0.54 vs 0.49) and novices (0.50 vs 0.47) and at CT (0.56 vs 0.51) and MRI (0.52 vs 0.43). Nine percent of masses prospectively considered cystic using Bosniak version 2005 criteria were considered solid using version 2019 criteria. In general, masses were more commonly classified in lower categories when radiologists used Bosniak version 2019 criteria compared with version 2005 criteria. The sole predictor of dispersion in Bosniak version 2019 class assignment was dispersion in septa or wall quality (ie, smooth vs irregular thickening vs nodule; 72% [MRI] and 60% [CT] overall model variance explained; multivariable P < .001). Conclusion Overall interrater agreement was similar between Bosniak version 2019 and version 2005; disagreements in septa or wall quality were common and strongly predictive of variation in Bosniak class assignment. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Eberhardt in this issue.

Abdominal CT in COVID-19 patients: incidence, indications, and findings.

PURPOSE: The purpose of this study was to evaluate the frequency, indications, and findings of abdominal CTs ordered in the initial evaluation of patients who had a positive COVID-19 test performed in our institution. METHODS: Retrospective chart review was performed on all patients who had a positive test for COVID-19 performed at a single quaternary care center from 1/20/2020 through 5/8/2020. In a subset of patients undergoing abdominal CT as part of the initial evaluation, the demographics, suspected COVID-19 status at the time of scan, presenting complaints, and abdominal CT findings were recorded. Cardiothoracic radiologists reviewed and scored the visualized lung bases for the likelihood of COVID-19. RESULTS: Only 43 (4.1%) of 1057 COVID-19 patients presented with abdominal complaints sufficient to warrant an abdominal CT. Of these 43 patients, the vast majority (39, 91%) were known or suspected to have COVID-19 at the time of the scan. Most (27/43, 63%) scans showed no acute abdominal abnormality, and those that were positive did not share a discernable pattern of abnormalities. Lung base abnormalities were common, and there was moderate inter-reviewer reliability. CONCLUSION: A minority of COVID-19 patients present with abdominal complaints sufficient to warrant a dedicated CT of the abdomen, and most of these studies will be negative or have abdominal findings not associated with COVID-19. Appropriate lung base findings are a more consistent indication of COVID-19 infection than abdominal findings.

Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support.

We evaluated the intraobserver variability of physicians aided by a computerized decision-support system for treatment response assessment (CDSS-T) to identify patients who show complete response to neoadjuvant chemotherapy for bladder cancer, and the effects of the intraobserver variability on physicians' assessment accuracy. A CDSS-T tool was developed that uses a combination of deep learning neural network and radiomic features from computed tomography (CT) scans to detect bladder cancers that have fully responded to neoadjuvant treatment. Pre- and postchemotherapy CT scans of 157 bladder cancers from 123 patients were collected. In a multireader, multicase observer study, physician-observers estimated the likelihood of pathologic T0 disease by viewing paired pre/posttreatment CT scans placed side by side on an in-house-developed graphical user interface. Five abdominal radiologists, 4 diagnostic radiology residents, 2 oncologists, and 1 urologist participated as observers. They first provided an estimate without CDSS-T and then with CDSS-T. A subset of cases was evaluated twice to study the intraobserver variability and its effects on observer consistency. The mean areas under the curves for assessment of pathologic T0 disease were 0.85 for CDSS-T alone, 0.76 for physicians without CDSS-T and improved to 0.80 for physicians with CDSS-T (P = .001) in the original evaluation, and 0.78 for physicians without CDSS-T and improved to 0.81 for physicians with CDSS-T (P = .010) in the repeated evaluation. The intraobserver variability was significantly reduced with CDSS-T (P < .0001). The CDSS-T can significantly reduce physicians' variability and improve their accuracy for identifying complete response of muscle-invasive bladder cancer to neoadjuvant chemotherapy.

Diagnostic Accuracy of CT for Prediction of Bladder Cancer Treatment Response with and without Computerized Decision Support.

RATIONALE AND OBJECTIVES: To evaluate whether a computed tomography (CT)-based computerized decision-support system for muscle-invasive bladder cancer treatment response assessment (CDSS-T) can improve identification of patients who have responded completely to neoadjuvant chemotherapy. MATERIALS AND METHODS: Following Institutional Review Board approval, pre-chemotherapy and post-chemotherapy CT scans of 123 subjects with 157 muscle-invasive bladder cancer foci were collected retrospectively. CT data were analyzed with a CDSS-T that uses a combination of deep-learning convolutional neural network and radiomic features to distinguish muscle-invasive bladder cancers that have fully responded to neoadjuvant treatment from those that have not. Leave-one-case-out cross-validation was used to minimize overfitting. Five attending abdominal radiologists, four diagnostic radiology residents, two attending oncologists, and one attending urologist estimated the likelihood of pathologic T0 disease (complete response) by viewing paired pre/post-treatment CT scans placed side-by-side on an internally-developed graphical user interface. The observers provided an estimate without use of CDSS-T and then were permitted to revise their estimate after a CDSS-T-derived likelihood score was displayed. Observer estimates were analyzed with multi-reader, multi-case receiver operating characteristic methodology. The area under the curve (AUC) and the statistical significance of the difference were estimated. RESULTS: The mean AUCs for assessment of pathologic T0 disease were 0.80 for CDSS-T alone, 0.74 for physicians not using CDSS-T, and 0.77 for physicians using CDSS-T. The increase in the physicians' performance was statistically significant (P < .05). CONCLUSION: CDSS-T improves physician performance for identifying complete response of muscle-invasive bladder cancer to neoadjuvant chemotherapy.

A pictorial review of bladder cancer nodal metastases.

Lymph node involvement in bladder cancer is common and has prognostic implications. Early and accurate identification of metastatic lymph nodes is, therefore, important in ensuring appropriate patient triage and management. The purpose of this review is to provide a pictorial and educational overview of the staging and imaging appearance of metastatic lymph nodes in bladder cancer. Additionally, a secondary aim of this manuscript is to provide a review of the diagnostic accuracy of common imaging modalities available for detecting metastatic lymph nodes in affected patients.

MR enterography-histology comparison in resected pediatric small bowel Crohn disease strictures: can imaging predict fibrosis?

BACKGROUND: Crohn disease is a chronic inflammatory condition that can lead to intestinal strictures. The presence of fibrosis within strictures alters optimal management but is not reliably detected by current imaging methods. OBJECTIVE: To correlate the MRI features of surgically resected small-bowel strictures in pediatric Crohn disease with histological inflammation and fibrosis scoring. MATERIALS AND METHODS: We included children with Crohn disease who had symptomatic small-bowel strictures requiring surgical resection and had preoperative MR enterography (MRE) within 3 months of surgery (n = 20). Two blinded radiologists reviewed MRE examinations to document stricture-related findings. A pediatric pathologist scored stricture histological specimens for fibrosis (0-4) and inflammation (0-4). MRE findings were correlated with histological data using Spearman correlation (ρ) and exact logistic regression analysis. RESULTS: There was significant positive correlation between histological bowel wall fibrosis and inflammation in resected strictures (ρ = 0.55; P = 0.01). Confluent transmural histological fibrosis was associated with pre-stricture upstream small-bowel dilatation >3 cm at univariate (odds ratio [OR] = 51.7; 95% confidence interval [CI]: 7.6- > 999.9; P = 0.0002) and multivariate (OR = 43.4; 95% CI: 6.1- > 999.9; P = 0.0006, adjusted for age) analysis. The degree of bowel wall T2-weighted signal intensity failed to correlate with histological bowel wall fibrosis or inflammation (P-values >0.05). There were significant negative correlations between histological fibrosis score and patient age at resection (ρ = -0.48, P = 0.03), and time from diagnosis to surgery (ρ = -0.73, P = 0.0002). CONCLUSION: Histological fibrosis and inflammation co-exist in symptomatic pediatric Crohn disease small-bowel strictures and are positively correlated. Pre-stenotic upstream small-bowel dilatation greater than 3 cm is significantly associated with confluent transmural fibrosis.

Systems biology of human epilepsy applied to patients with brain tumors.

Epilepsy is a disease of recurrent seizures that can be associated with a wide variety of acquired and developmental brain lesions. Current medications for patients with epilepsy can suppress seizures; they do not cure or modify the underlying disease process. On the other hand, surgical removal of focal brain regions that produce seizures can be curative. This surgical procedure can be more precise with the placement of intracranial recording electrodes to identify brain regions that generate seizure activity as well as those that are critical for normal brain function. The detail that goes into these surgeries includes extensive neuroimaging, electrophysiology, and clinical data. Combined with precisely localized tissues removed, these data provide an unparalleled opportunity to learn about the interrelationships of many "systems" in the human brain not possible in just about any other human brain disorder. Herein, we describe a systems biology approach developed to study patients who undergo brain surgery for epilepsy and how we have begun to apply these methods to patients whose seizures are associated with brain tumors. A central goal of this clinical and translational research program is to improve our understanding of epilepsy and brain tumors and to improve diagnosis and treatment outcomes of both.

Electrical, molecular and behavioral effects of interictal spiking in the rat.

OBJECTIVE: Epilepsy is a disease characterized by chronic seizures, but is associated with significant comorbidities between seizures including cognitive impairments, hyperactivity, and depression. To study this interictal state, we characterized the electrical, molecular, and behavior effects of chronic, neocortical interictal spiking in rats. METHODS: A single injection of tetanus toxin into somatosensory cortex generated chronic interictal spiking measured by long-term video EEG monitoring and was correlated with motor activity. The cortical pattern of biomarker activation and the effects of blocking MAPK signaling on interictal spiking and behavior were determined. RESULTS: Interictal spiking in this model increases in frequency, size, and becomes repetitive over time, but is rarely associated with seizures. Interictal spiking was sufficient to produce the same molecular and cellular pattern of layer 2/3-specific CREB activation and plasticity gene induction as is seen in the human interictal state. Increasing spike frequency was associated with hyperactivity, demonstrated by increased ambulatory activity and preferential circling toward the spiking hemisphere. Loud noises induced epileptic discharges, identical to spontaneous discharges. Treatment with a selective MAPK inhibitor prevented layer 2/3 CREB activation, reduced the frequency of epileptic discharges, and normalized behavioral abnormalities, but had no effect on seizures induced by electrical kindling. INTERPRETATION: These results provide insights into the development of interictal epileptic spiking, their relationship to behavior, and suggest that interictal and ictal activities utilize distinct molecular pathways. This model, that parallels recent observations in humans, will be useful to develop therapeutics against interictal spiking and its behavioral comorbidities.

High inter-reviewer variability of spike detection on intracranial EEG addressed by an automated multi-channel algorithm.

OBJECTIVE: The goal of this study was to determine the consistency of human reviewer spike detection and then develop a computer algorithm to make the intracranial spike detection process more objective and reliable. METHODS: Three human reviewers marked interictal spikes on samples of intracranial EEGs from 10 patients. The sensitivity, precision and agreement in channel ranking by activity were calculated between reviewers. A computer algorithm was developed to parallel the way human reviewers detect spikes by first identifying all potential spikes on each channel using frequency filtering and then block scaling all channels at the same time in order to exclude potential spikes that fall below an amplitude and slope threshold. Its performance was compared to the human reviewers on the same set of patients. RESULTS: Human reviewers showed surprisingly poor inter-reviewer agreement, but did broadly agree on the ranking of channels for spike activity. The computer algorithm performed as well as the human reviewers and did especially well at ranking channels from highest to lowest spike frequency. CONCLUSIONS: Our algorithm showed good agreement with the different human reviewers, even though they demonstrated different criteria for what constitutes a 'spike' and performed especially well at the clinically important task of ranking channels by spike activity. SIGNIFICANCE: An automated, objective method to detect interictal spikes on intracranial recordings will improve both research and the surgical management of epilepsy patients.