Early silent coronary bypass graft occlusion following coronary bypass surgery, implication of routine coronary computed tomography angiography.

Objective: To evaluate incidence and predictors of early silent bypass occlusion following coronary bypass surgery using cardiac computed tomography angiography. Methods: A total of 439 consecutive patients with mean age of 66 ± 10 years comprising 17% (n = 75) females underwent isolated coronary bypass surgery followed by CT scan before discharge. Graft patency was evaluated in 1,319 anastomoses where 44% (n = 580) arterial and 56% (n = 739) vein graft anastomosis were performed. Cardiovascular risk factors, demographics, and intraoperative variables were analyzed. We conducted univariable and multivariable logistic regression analyses to analyze variables potentially associated with graft occlusion following CABG. Variables included gender, surgery duration, graft flow, pulsatility index, vein vs. artery graft, and recent MI. Results: Overall incidence of graft occlusion was 2.4% (31/1,319), and it was diagnosed in 6.6% (29/439) of patients. The difference in occlusion between arterial (2.1%) and vein (2.6%) grafts was not significant, p = 0.68. The duration of intervention p = 0.034, cross clamp time p = 0.024 as well the number of distal anastomosis p = 0.034 were significantly higher in occlusion group. The univariate and multivariate logistic regression indicated duration of surgery being predictive for bypass graft occlusion with OR = 1.18; 95% CI: 1.01-1.38; p = 0.035. Conclusions: Early graft occlusion was associated with surgical factors. The number of distant anastamoses, along duration of surgical intervention were, significantly influenced the risk of EGO. Prolonged procedural time reflecting complex coronary pathology and time-consuming revascularization procedure was as well associated to the elevated risk of occlusion.

Imaging to predict early relapses after treatment discontinuation in patients with large vessel giant cell arteritis - A cohort study.

OBJECTIVES: To investigate the value of [18F]fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) in predicting relapse after treatment discontinuation in patients with large-vessel giant cell arteritis (LV-GCA). METHODS: This study included patients with LV-GCA whose treatment was discontinued between 2018 and 2023. All patients underwent PET/CT and/or MRI at the time of treatment discontinuation in clinical remission. Qualitative and quantitative PET/CT scores, by measuring standardized uptake values (SUV), and semiquantitative MRI scores of the aorta and supraaortic vessels were compared between patients who relapsed within 4 months after treatment discontinuation and those who did not. RESULTS: Forty patients were included (median age 67.4 years, interquartile range (IQR) 60.8-74.0; 77.5 % females). Eleven patients (27.5 %) relapsed after treatment discontinuation (time to relapse 1.9 months, IQR 1.4-3.3). Patients who relapsed were comparable to those who remained in remission with respect to the presence of active vasculitis on MRI and/or PET/CT (54.5% vs. 58.6 %, p = 1.0), the number of segments with vasculitic findings on MRI (0, IQR 0.0-1.5, vs. 2, IQR 0.0-3.0, p = 0.221) or the highest SUV artery/liver ratio on PET/CT (1.5, IQR 1.4-1.6, vs. 1.3, IQR 1.2-1.6, p = 0.505). The median number of vasculitic segments on PET/CT was 2.5 (IQR 0.5-4.5) in those with vs. 0 (IQR 0.0-1.5, p = 0.085) in those without relapse, and the PET/CT scores 4.5 (IQR 0.75-8.25) vs. 0 (IQR 0.0-3.0, p = 0.172). CONCLUSION: PET/CT or MRI at treatment stop did not predict relapse and may not be suited to guide treatment decisions in patients with LV-GCA in remission.

Associations between 3D-based Left Atrial Volumetric and Blood Flow Parameters in a Single-Site Cohort of the Multi-Ethnic Study of Atherosclerosis.

Purpose To investigate associations between left atrial volume (LAV) and function with impaired three-dimensional hemodynamics from four-dimensional flow MRI. Materials and Methods A subcohort of participants from the Multi-Ethnic Study of Atherosclerosis from Northwestern University underwent prospective 1.5-T cardiac MRI including whole-heart four-dimensional flow and short-axis cine imaging between 2019 and 2020. Four-dimensional flow MRI analysis included manual three-dimensional segmentations of the LA and LA appendage (LAA), which were used to quantify LA and LAA peak velocity and blood stasis (% voxels < 0.1 m/sec). Short-axis cine data were used to delineate LA contours on all cardiac time points, and the resulting three-dimensional-based LAVs were extracted for calculation of LA emptying fractions (LAEFtotal, LAEFactive, LAEFpassive). Stepwise multivariable linear models were calculated for each flow parameter (LA stasis, LA peak velocity, LAA stasis, LAA peak velocity) to determine associations with LAV and LAEF. Results This study included 158 participants (mean age, 73 years ± 7 [SD]; 83 [52.5%] female and 75 [47.4%] male participants). In multivariable models, a 1-unit increase of LAEFtotal was associated with decreased LA stasis (ß coefficient, -0.47%; P < .001), while increased LAEFactive was associated with increased LA peak velocity (ß coefficient, 0.21 cm/sec; P < .001). Furthermore, increased minimum LAV indexed was most associated with impaired LAA flow (higher LAA stasis [ß coefficient, 0.65%; P < .001] and lower LAA peak velocity [ß coefficient, -0.35 cm/sec; P < .001]). Conclusion Higher minimum LAV and reduced LA function were associated with impaired flow characteristics in the LA and LAA. LAV assessment might therefore be a surrogate measure for LA and LAA flow abnormalities. Keywords: Atherosclerosis, Left Atrial Volume, Left Atrial Blood Flow, 4D Flow MRI Supplemental material is available for this article. © RSNA, 2024.

MRI Investigation of the Association of Left Atrial and Left Atrial Appendage Hemodynamics with Silent Brain Infarction.

BACKGROUND: Left atrial (LA) myopathy is thought to be associated with silent brain infarctions (SBI) through changes in blood flow hemodynamics leading to thrombogenesis. 4D-flow MRI enables in-vivo hemodynamic quantification in the left atrium (LA) and LA appendage (LAA). PURPOSE: To determine whether LA and LAA hemodynamic and volumetric parameters are associated with SBI. STUDY TYPE: Prospective observational study. POPULATION: A single-site cohort of 125 Participants of the multiethnic study of atherosclerosis (MESA), mean age: 72.3 ± 7.2 years, 56 men. FIELD STRENGTH/SEQUENCE: 1.5T. Cardiac MRI: Cine balanced steady state free precession (bSSFP) and 4D-flow sequences. Brain MRI: T1- and T2-weighted SE and FLAIR. ASSESSMENT: Presence of SBI was determined from brain MRI by neuroradiologists according to routine diagnostic criteria in all participants without a history of stroke based on the MESA database. Minimum and maximum LA volumes and ejection fraction were calculated from bSSFP data. Blood stasis (% of voxels <10 cm/sec) and peak velocity (cm/sec) in the LA and LAA were assessed by a radiologist using an established 4D-flow workflow. STATISTICAL TESTS: Student's t test, Mann-Whitney U test, one-way ANOVA, chi-square test. Multivariable stepwise logistic regression with automatic forward and backward selection. Significance level P < 0.05. RESULTS: 26 (20.8%) had at least one SBI. After Bonferroni correction, participants with SBI were significantly older and had significantly lower peak velocities in the LAA. In multivariable analyses, age (per 10-years) (odds ratio (OR) = 1.99 (95% confidence interval (CI): 1.30-3.04)) and LAA peak velocity (per cm/sec) (OR = 0.87 (95% CI: 0.81-0.93)) were significantly associated with SBI. CONCLUSION: Older age and lower LAA peak velocity were associated with SBI in multivariable analyses whereas volumetric-based measures from cardiac MRI or cardiovascular risk factors were not. Cardiac 4D-flow MRI showed potential to serve as a novel imaging marker for SBI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Robust and fast stochastic 4D flow vector-field signature technique for quantifying composite flow dynamics from 4D flow MRI: Application to left atrial flow in atrial fibrillation.

4D flow MRI is an emerging imaging modality that maps voxel-wise blood flow information as velocity vector fields that is acquired in 7-dimensional image volumes (3 spatial dimensions + 3 velocity directions + time). Blood flow in the cardiovascular system is often complex and composite involving multiple flow dynamics and patterns (e.g., vortex flow, jets, stagnating flow) that occur and interact simultaneously. The spectrum of such complex flow dynamics is embedded in the velocity vector field dynamics derived from 4D Flow MRI. However, current flow metrics cannot fully measure high-dimensional vector-field data and embedded complex composite flow data. Instead, these methods need to break down the vector-field data into secondary scalar fields of individual flow components using fluid dynamics operators. These methods are gradient-based and sensitive to data uncertainties, and only focus on individual flow components of the overall composite flow, therefore potentially underestimating the severity of overall flow changes associated with cardiovascular diseases. To address these limitations, in MICCAI 2021, we introduced a novel comprehensive stochastic 4D Flow vector-field signature technique that works directly on the entire spatiotemporal velocity vector field. This technique uses efficient stochastic gradient-free interrogation of multi-million flow vector-pairs per patient to derive the patient's unique flow profile of the complex composite flow alterations and in real-time processing. The signature technique's probabilistic gradient-free formulation should allow for highly robust quantification despite inherent errors in 4D flow MRI acquisitions. Here, we extend the application of the 4D flow vector-field signature technique to the left atrium to analyze complex composite flow changes in patients with atrial fibrillation. In 128 subjects, we performed extensive sensitivity testing and determined that the vector-field signature technique is highly robust to typical sources of data uncertainties in 4D flow MRI: degradation in spatiotemporal resolution, added Gaussian noise, and segmentation errors. We demonstrate the excellent generalizability of the stochastic convergence from the aorta to the left atrium and between different 4D Flow MRI acquisition protocols. We compare the robustness of our technique to existing advanced flow quantification metrics of kinetic energy, vorticity, and energy loss demonstrating a superior performance of up-to 14-fold. Our results show the potential diagnostic and clinical utility of our signature technique in identifying distinctly altered composite flow signatures in atrial fibrillation patients independent of existing flow metrics.

Magnetic Resonance Imaging Findings Corresponding to Vasculitis as Defined via [18F]FDG Positron Emission Tomography or Ultrasound.

Background: We sought to investigate magnetic resonance imaging (MRI) parameters that correspond to vasculitis observed via [18F]FDG positron emission tomography/computed tomography (PET/CT) and ultrasound in patients with large-vessel giant cell arteritis (LV-GCA). Methods: We performed a cross-sectional analysis of patients diagnosed with LV-GCA. Patients were selected if MRI, PET/CT, and vascular ultrasound were performed at the time of LV-GCA diagnosis. Imaging findings in vessel segments (axillary segment per side, thoracic aorta) assessed using at least two methods were compared. Vessel wall thickening, oedema, and contrast agent enhancement were each assessed via MRI. Results: Twelve patients with newly diagnosed LV-GCA were included (seven females, 58%; median age 72.1, IQR 65.5-74.2 years). The MRI results showed mural thickening in 9/24 axillary artery segments. All but 1 segment showed concomitant oedema, and additional contrast enhancement was found in 3/9 segments. In total, 8 of these 9 segments corresponded to vasculitic findings in the respective segments as observed via PET/CT, and 2/9 corresponded to vasculitis in the respective ultrasound images. If MRI was performed more than 6 days after starting prednisone treatment, thickening and oedema were seen in only 1/24 segments, which was also pathologic according to ultrasound findings but not those obtained via PET/CT. Four patients had mural thickening, oedema, and contrast enhancement in the aorta, among whom three patients also had vasculitic findings observed via PET/CT. Isolated mural thickening in one patient corresponded to a negative PET/CT result. Conclusions: In the MRI results, mural thickening due to oedema corresponded to vasculitic PET/CT findings but not vasculitic ultrasound findings. The duration of steroid treatment may reduce the sensitivity of MRI.

MRI Quantification of Left Atrial Circumferential Strain in Mitral Regurgitation: A Feasibility and Reproducibility Study.

BACKGROUND: MRI-derived left atrial (LA) longitudinal strain has been shown to be a marker for mitral regurgitation, but the utility of LA circumferential strain remains unclear. PURPOSE: To assess feasibility and reproducibility of LA circumferential strain, identify changes in mitral regurgitation patients compared to healthy volunteers, and determine strain's association with mitral regurgitation severity and cardiac function. STUDY TYPE: Retrospective. POPULATION: 52 mitral regurgitation patients, 12 healthy volunteers. FIELD STRENGTH/SEQUENCE: Steady-state free precession cine and 2D phase contrast sequences at 1.5T. ASSESSMENT: Peak LA circumferential strain was computed in each of three short-axis slices (superior, mid, and inferior) and longitudinal strain computed from long-axis slices using MRI feature-tracking software. Strain test-retest reproducibility was determined from two repeat studies in healthy volunteers. STATISTICAL TESTS: LA circumferential strain test-retest reproducibility was assessed by intra-class correlation coefficient (ICC). Strain was compared between cohorts using Student's t-test or Mann-Whitney U. Mitral regurgitation severity association with strain and LV function was assessed using Spearman correlation and multivariable regression. Significance was defined as P < 0.05. RESULTS: LA circumferential strain assessment was feasible in all subjects with moderate reproducibility in the superior (ICC = 0.74), mid LA (ICC = 0.71), and inferior LA (ICC = 0.63). In mitral regurgitation patients, LA circumferential strain was significantly lower in the superior (11.86% [6.5%,19.2%] vs. 18.73% ± 6.7%) and mid LA slices (18.41% ± 9.5% vs. 28.7% ± 10.4%) compared to healthy volunteers. Mitral regurgitation severity significantly associated with mid LA circumferential strain (ß = -0.03) and LAV significantly associated with superior LA circumferential strain (ß = -2.09), both independent of LA longitudinal strain and CO. DATA CONCLUSION: LA circumferential strain assessment is feasible with moderate reproducibility. Compared to healthy volunteers, patients had significantly lower LA circumferential strain. Mitral regurgitation severity and LAV were significantly associated with LA circumferential strain independent of LA longitudinal strain. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images.

Purpose: To present a deep learning segmentation model that can automatically and robustly segment all major anatomic structures on body CT images. Materials and Methods: In this retrospective study, 1204 CT examinations (from 2012, 2016, and 2020) were used to segment 104 anatomic structures (27 organs, 59 bones, 10 muscles, and eight vessels) relevant for use cases such as organ volumetry, disease characterization, and surgical or radiation therapy planning. The CT images were randomly sampled from routine clinical studies and thus represent a real-world dataset (different ages, abnormalities, scanners, body parts, sequences, and sites). The authors trained an nnU-Net segmentation algorithm on this dataset and calculated Dice similarity coefficients to evaluate the model's performance. The trained algorithm was applied to a second dataset of 4004 whole-body CT examinations to investigate age-dependent volume and attenuation changes. Results: The proposed model showed a high Dice score (0.943) on the test set, which included a wide range of clinical data with major abnormalities. The model significantly outperformed another publicly available segmentation model on a separate dataset (Dice score, 0.932 vs 0.871; P < .001). The aging study demonstrated significant correlations between age and volume and mean attenuation for a variety of organ groups (eg, age and aortic volume [rs = 0.64; P < .001]; age and mean attenuation of the autochthonous dorsal musculature [rs = -0.74; P < .001]). Conclusion: The developed model enables robust and accurate segmentation of 104 anatomic structures. The annotated dataset (https://doi.org/10.5281/zenodo.6802613) and toolkit (https://www.github.com/wasserth/TotalSegmentator) are publicly available.Keywords: CT, Segmentation, Neural Networks Supplemental material is available for this article. © RSNA, 2023See also commentary by Sebro and Mongan in this issue.

Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT.

PURPOSE/OBJECTIVE: Reliable detection of thoracic aortic dilatation (TAD) is mandatory in clinical routine. For ECG-gated CT angiography, automated deep learning (DL) algorithms are established for diameter measurements according to current guidelines. For non-ECG gated CT (contrast enhanced (CE) and non-CE), however, only a few reports are available. In these reports, classification as TAD is frequently unreliable with variable result quality depending on anatomic location with the aortic root presenting with the worst results. Therefore, this study aimed to explore the impact of re-training on a previously evaluated DL tool for aortic measurements in a cohort of non-ECG gated exams. METHODS & MATERIALS: A cohort of 995 patients (68 ± 12 years) with CE (n = 392) and non-CE (n = 603) chest CT exams was selected which were classified as TAD by the initial DL tool. The re-trained version featured improved robustness of centerline fitting and cross-sectional plane placement. All cases were processed by the re-trained DL tool version. DL results were evaluated by a radiologist regarding plane placement and diameter measurements. Measurements were classified as correctly measured diameters at each location whereas false measurements consisted of over-/under-estimation of diameters. RESULTS: We evaluated 8948 measurements in 995 exams. The re-trained version performed 8539/8948 (95.5%) of diameter measurements correctly. 3765/8948 (42.1%) of measurements were correct in both versions, initial and re-trained DL tool (best: distal arch 655/995 (66%), worst: Aortic sinus (AS) 221/995 (22%)). In contrast, 4456/8948 (49.8%) measurements were correctly measured only by the re-trained version, in particular at the aortic root (AS: 564/995 (57%), sinotubular junction: 697/995 (70%)). In addition, the re-trained version performed 318 (3.6%) measurements which were not available previously. A total of 228 (2.5%) cases showed false measurements because of tilted planes and 181 (2.0%) over-/under-segmentations with a focus at AS (n = 137 (14%) and n = 73 (7%), respectively). CONCLUSION: Re-training of the DL tool improved diameter assessment, resulting in a total of 95.5% correct measurements. Our data suggests that the re-trained DL tool can be applied even in non-ECG-gated chest CT including both, CE and non-CE exams.

Aortic arch and frozen elephant trunk repair of a right-sided aortic arch with pseudoaneurysm rupture.

A 53-year-old man with a history of vascular ring repair secondary to a right-sided aortic arch with a retroesophageal subclavian artery and ligamentum arteriosum to the descending thoracic aorta presented to our institution with a large aortic pseudoaneurysm of the distal aortic arch. Computed tomography demonstrated a right-sided aortic arch with a 5.8-cm pseudoaneurysm arising from the distal arch with concern for rupture. The patient underwent successful two-stage repair, including a left carotid artery to subclavian artery bypass, followed by total arch replacement with the frozen elephant trunk technique. He recovered well postoperatively, and computed tomography showed complete, successful repair of the pseudoaneurysm.

Comparison of Biplane Area-Length Method and 3D Volume Quantification by Using Cardiac MRI for Assessment of Left Atrial Volume in Atrial Fibrillation.

Purpose: To compare maximum left atrial (LA) volume (LAV) from the routinely used biplane area-length (BAL) method with three-dimensional (3D)-based volumetry from late gadolinium-enhanced MRI (3D LGE MRI) and contrast-enhanced MR angiography (3D CE-MRA) in patients with atrial fibrillation (AF). Materials and Methods: Sixty-four patients with AF (mean age, 63 years ± 9 [SD]; 40 male patients) were retrospectively included from a prospective cohort acquired between October 2018 and February 2021. All patients underwent a research MRI examination that included standard two- and four-chamber cine acquisitions, 3D CE-MRA, and 3D LGE MRI performed prior to the atrial kick. Contour delineation on cine imaging and LA 3D segmentations were performed by a radiologist. Maximum LAV (BALmax) was extracted from the BAL volume-time curve and compared with LAV from 3D CE-MRA and 3D LGE MRI. The Kruskal-Wallis test was performed, followed by the Dunn post hoc test and Bland-Altman analyses. Interobserver variability was assessed in 10 patients. Results: BALmax underestimated LAV compared with 3D CE-MRA (bias: -23.5 mL ± 46.2, P < .001) and 3D LGE MRI (bias: -31.3 mL ± 58.3, P < .001), whereas 3D LGE MRI volumes showed no evidence of a difference from 3D CE-MRA (bias: 7.8 mL ± 45.7, P = .38). Interobserver variability yielded excellent agreement for each method (intraclass correlation coefficient, 0.96-0.98). Conclusion: BALmax underestimated LAV in patients with AF compared with 3D LGE MRI and 3D CE-MRA, suggesting that the geometric assumption of an ellipsoidal LA shape in BAL does not reflect LA geometry in patients with AF.Keywords: Left Atrial Volume, Biplane Area-Length, Late Gadolinium-enhanced 3D MRI, Contrast-enhanced 3D MR Angiography, Atrial Fibrillation Supplemental material is available for this article. © RSNA, 2023.

Quantification of left atrial function by the area-length method overestimates left atrial emptying fraction.

PURPOSE: The biplane area-length method is commonly used in cardiac magnetic resonance (CMR) to assess left atrial (LA) volume (LAV) and function. Associations between left atrial emptying fraction (LAEF) and clinical outcomes have been reported. However, only limited data are available on the calculation of LAEF using the biplane method compared to 3D assessment. This study aimed to compare volumetric and functional LA parameters obtained from the biplane method with 3D assessment in a large, multiethnic cohort. METHOD: 158 participants of MESA (Multi-Ethnic Study of Atherosclerosis) underwent CMR that included standard two- and four-chamber steady-state free precession (SSFP) cine imaging for the biplane method. For 3D-based assessment, short-axis SSFP cine series covering the entire LA were obtained, followed by manual delineation of LA contours to create a time-resolved 3D LAV dataset. Paired t-tests and Bland-Altman plots were used to analyze the data. RESULTS: Standard volumetric assessment showed that LAVmin (bias: -8.35 mL, p < 0.001), LAVmax (bias: -9.38 mL, p < 0.001) and LAVpreA (bias: -10.27 mL, p < 0.001) were significantly smaller using the biplane method compared to 3D assessment. Additionally, the biplane method reported significantly higher LAEFtotal (bias: 7.22 %, p < 0.001), LAEFactive (bias: 6.08 %, p < 0.001), and LAEFpassive (bias: 4.51 %, p < 0.001) with wide limits of agreement. CONCLUSIONS: LA volumes were underestimated using the biplane method compared to 3D assessment, while LAEF parameters were overestimated. These findings demonstrate a lack of precision using the biplane method for LAEF assessment. Our results support the usage of 3D assessment in specific settings when LA volumetric and functional parameters are in focus.

Fully-automated deep learning-based flow quantification of 2D CINE phase contrast MRI.

OBJECTIVES: Time-resolved, 2D-phase-contrast MRI (2D-CINE-PC-MRI) enables in vivo blood flow analysis. However, accurate vessel contour delineation (VCD) is required to achieve reliable results. We sought to evaluate manual analysis (MA) compared to the performance of a deep learning (DL) application for fully-automated VCD and flow quantification and corrected semi-automated analysis (corSAA). METHODS: We included 97 consecutive patients (age = 52.9 ± 16 years, 41 female) with 2D-CINE-PC-MRI imaging on 1.5T MRI systems at sinotubular junction (STJ), and 28/97 also received 2D-CINE-PC at main pulmonary artery (PA). A cardiovascular radiologist performed MA (reference) and corSAA (built-in tool) in commercial software for all cardiac time frames (median: 20, total contours per analysis: 2358 STJ, 680 PA). DL-analysis automatically performed VCD, followed by net flow (NF) and peak velocity (PV) quantification. Contours were compared using Dice similarity coefficients (DSC). Discrepant cases (> ± 10 mL or > ± 10 cm/s) were reviewed in detail. RESULTS: DL was successfully applied to 97% (121/125) of the 2D-CINE-PC-MRI series (STJ: 95/97, 98%, PA: 26/28, 93%). Compared to MA, mean DSC were 0.91 ± 0.02 (DL), 0.94 ± 0.02 (corSAA) at STJ, and 0.85 ± 0.08 (DL), 0.93 ± 0.02 (corSAA) at PA; this indicated good to excellent DL-performance. Flow quantification revealed similar NF at STJ (p = 0.48) and PA (p > 0.05) between methods while PV assessment was significantly different (STJ: p < 0.001, PA: p = 0.04). A detailed review showed noisy voxels in MA and corSAA impacted PV results. Overall, DL analysis compared to human assessments was accurate in 113/121 (93.4%) cases. CONCLUSIONS: Fully-automated DL-analysis of 2D-CINE-PC-MRI provided flow quantification at STJ and PA at expert level in > 93% of cases with results being available instantaneously. KEY POINTS: • Deep learning performed flow quantification on clinical 2D-CINE-PC series at the sinotubular junction and pulmonary artery at the expert level in > 93% of cases. • Location detection and contouring of the vessel boundaries were performed fully-automatic with results being available instantaneously compared to human assessments which approximately takes three minutes per location. • The evaluated tool indicates usability in daily practice.

Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center.

Rationale and objective: In this study, we evaluate the ability of a novel cloud-based radiology analytics platform to continuously monitor imaging volumes at a large tertiary center following institutional protocol and policy changes. Materials and methods: We evaluated response to environmental factors through the lens of the COVID-19 pandemic. Analysis involved 11 CT/18 MR imaging systems at a large tertiary center. A vendor neutral, cloud-based analytics tool (CBRAP) was used to retrospectively collect information via DICOM headers on imaging exams between Oct. 2019 to Aug. 2021. Exams were stratified by modality (CT or MRI) and organized by body region. Pre-pandemic scan volumes (Oct 2019-Feb. 2010) were compared with volumes during/after two waves of COVID-19 in Illinois (Mar. to May 2020 & Oct. to Dec. 2020) using a t-test or Mann-Whitney U test. Results: The CBRAP was able to analyze 169,530 CT and 110,837 MR images, providing a detailed snapshot of baseline and post-pandemic CT and MR imaging across the radiology enterprise at our tertiary center. The CBRAP allowed for further subdivision in its reporting, showing monthly trends in average scan volumes specifically in the head, abdomen, spine, MSK, thorax, neck, GU system, or breast. Conclusion: The CBRAP retrieved data for 300,000 + imaging exams across multiple modalities at a large tertiary center in a highly populated, urban environment. The ability to analyze large imaging volumes across multiple waves of COVID-19 and evaluate quality-improvement endeavors/imaging protocol changes displays the usefulness of the CBRAP as an advanced imaging analytics tool.

Performance of a deep learning tool to detect missed aortic dilatation in a large chest CT cohort.

Purpose: Thoracic aortic (TA) dilatation (TAD) is a risk factor for acute aortic syndrome and must therefore be reported in every CT report. However, the complex anatomy of the thoracic aorta impedes TAD detection. We investigated the performance of a deep learning (DL) prototype as a secondary reading tool built to measure TA diameters in a large-scale cohort. Material and methods: Consecutive contrast-enhanced (CE) and non-CE chest CT exams with "normal" TA diameters according to their radiology reports were included. The DL-prototype (AIRad, Siemens Healthineers, Germany) measured the TA at nine locations according to AHA guidelines. Dilatation was defined as >45 mm at aortic sinus, sinotubular junction (STJ), ascending aorta (AA) and proximal arch and >40 mm from mid arch to abdominal aorta. A cardiovascular radiologist reviewed all cases with TAD according to AIRad. Multivariable logistic regression (MLR) was used to identify factors (demographics and scan parameters) associated with TAD classification by AIRad. Results: 18,243 CT scans (45.7% female) were successfully analyzed by AIRad. Mean age was 62.3 ± 15.9 years and 12,092 (66.3%) were CE scans. AIRad confirmed normal diameters in 17,239 exams (94.5%) and reported TAD in 1,004/18,243 exams (5.5%). Review confirmed TAD classification in 452/1,004 exams (45.0%, 2.5% total), 552 cases were false-positive but identification was easily possible using visual outputs by AIRad. MLR revealed that the following factors were significantly associated with correct TAD classification by AIRad: TAD reported at AA [odds ratio (OR): 1.12, p < 0.001] and STJ (OR: 1.09, p = 0.002), TAD found at >1 location (OR: 1.42, p = 0.008), in CE exams (OR: 2.1-3.1, p < 0.05), men (OR: 2.4, p = 0.003) and patients presenting with higher BMI (OR: 1.05, p = 0.01). Overall, 17,691/18,243 (97.0%) exams were correctly classified. Conclusions: AIRad correctly assessed the presence or absence of TAD in 17,691 exams (97%), including 452 cases with previously missed TAD independent from contrast protocol. These findings suggest its usefulness as a secondary reading tool by improving report quality and efficiency.

Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF. METHODS: We retrospectively analyzed consecutive AF patients who underwent cMRI on 1.5T systems including a stack of oblique-axial CINE series covering the whole LA. The LA was automatically segmented by a validated CNN. In the resulting volume-time curves, maximum, minimum and LAV before atrial contraction were automatically identified. Active, passive and total LA emptying fractions (LAEF) were calculated and compared to clinical classifications (AF Burden score (AFBS), increased stroke risk (CHA2DS2VASc≥2), AF type (paroxysmal/persistent), EHRA score, and AF risk factors). Moreover, multivariable linear regression models (mLRM) were used to identify associations with AF risk factors. RESULTS: Overall, 102 patients (age 61±9 years, 17% female) were analyzed. Active LAEF (LAEF_active) decreased significantly with an increase of AFBS (minimal: 44.0%, mild: 36.2%, moderate: 31.7%, severe: 20.8%, p<0.003) which was primarily caused by an increase of minimum LAV. Likewise, LAEF_active was lower in patients with increased stroke risk (30.7% vs. 38.9%, p = 0.002). AF type and EHRA score did not show significant differences between groups. In mLRM, a decrease of LAEF_active was associated with higher age (per year: -0.3%, p = 0.02), higher AFBS (per category: -4.2%, p<0.03) and heart failure (-12.1%, p<0.04). CONCLUSIONS: Fully-automatic morphometry of the whole LA derived from cMRI showed significant relationships between LAEF_active with increased stroke risk and severity of AFBS. Furthermore, higher age, higher AFBS and presence of heart failure were independent predictors of reduced LAEF_active, indicating its potential usefulness as an imaging biomarker.

Baseline 4D Flow-Derived in vivo Hemodynamic Parameters Stratify Descending Aortic Dissection Patients With Enlarging Aortas.

Purpose: The purpose of our study was to assess the value of true lumen and false lumen hemodynamics compared to aortic morphological measurements for predicting adverse-aorta related outcomes (AARO) and aortic growth in patients with type B aortic dissection (TBAD). Materials and Methods: Using an IRB approved protocol, we retrospectively identified patients with descending aorta (DAo) dissection at a large tertiary center. Inclusion criteria includes known TBAD with ≥ 6 months of clinical follow-up after initial presentation for TBAD or after ascending aorta intervention for patients with repaired type A dissection with residual type B aortic dissection (rTAAD). Patients with prior descending aorta intervention were excluded. The FL and TL of each patient were manually segmented from 4D flow MRI data, and 3D parametric maps of aortic hemodynamics were generated. Groups were divided based on (1) presence vs. absence of AARO and (2) growth rate ≥ vs. < 3 mm/year. True and false lumen kinetic energy (KE), stasis, peak velocity (PV), reverse/forward flow (RF/FF), FL to TL KE ratio, as well as index aortic diameter were compared between groups using the Mann-Whitney U or independent t-test. Results: A total of n = 51 patients (age: 58.4 ± 15.0 years, M/F: 31/20) were included for analysis of AARO. This group contained n = 26 patients with TBAD and n = 25 patients with rTAAD. In the overall cohort, AARO patients had larger baseline diameters, lower FL-RF, FL stasis, TL-KE, TL-FF and TL-PV. Among patients with de novo TBAD, those with AAROs had larger baseline diameter, lower FL stasis and TL-PV. In both the overall cohort and in the subgroup of de novo TBAD, subjects with aortic growth ≥ 3mm/year, patients had a higher KE ratio. Conclusion: Our study suggests that 4D flow MRI is a promising tool for TBAD evaluation that can provide information beyond traditional MRA or CTA. 4D flow has the potential to become an integral aspect of TBAD work-up, as hemodynamic assessment may allow earlier identification of at-risk patients who could benefit from earlier intervention.