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Background: Risk stratification, detection of minimal residual disease (MRD), and implementation of novel therapeutic agents have improved outcome in acute lymphoblastic leukemia (ALL), but survival of adult patients with T-cell acute lymphoblastic leukemia (T-ALL) remains unsatisfactory. Thus, novel molecular insights and therapeutic approaches are urgently needed.
Methods: We studied the impact of B-cell CLL/lymphoma 11b (BCL11b), a key regulator in normal T-cell development, in T-ALL patients enrolled into the German Multicenter Acute Lymphoblastic Leukemia Study Group trials (GMALL; n = 169). The mutational status (exon 4) of BCL11b was analyzed by Sanger sequencing and mRNA expression levels were determined by quantitative real-time PCR. In addition gene expression profiles generated on the Human Genome U133 Plus 2.0 Array (affymetrix) were used to investigate BCL11b low and high expressing T-ALL patients.
Results: We demonstrate that BCL11b is aberrantly expressed in T-ALL and gene expression profiles reveal an association of low BCL11b expression with up-regulation of immature markers. T-ALL patients characterized by low BCL11b expression exhibit an adverse prognosis [5-year overall survival (OS): low 35% (n = 40) vs. high 53% (n = 129), P = 0.02]. Within the standard risk group of thymic T-ALL (n = 102), low BCL11b expression identified patients with an unexpected poor outcome compared to those with high expression (5-year OS: 20%, n = 18 versus 62%, n = 84, P < 0.01). In addition, sequencing of exon 4 revealed a high mutation rate (14%) of BCL11b.
Conclusions: In summary, our data of a large adult T-ALL patient cohort show that low BCL11b expression was associated with poor prognosis; particularly in the standard risk group of thymic T-ALL. These findings can be utilized for improved risk prediction in a significant proportion of adult T-ALL patients, which carry a high risk of standard therapy failure despite a favorable immunophenotype.
Background: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans. Methods: One hundred patients (median age, 69 years; range, 19–94 years) who received CT scans of the thoracolumbar spine and blood-testing for hemoglobin and hematocrit levels ± 24 h between 08/2018 and 11/2019 were retrospectively included. Intraaortic blood was segmented using a spherical volume of interest of 1 cm diameter with consecutive radiomic analysis applying PyRadiomics software. Feature selection was performed applying analysis of correlation and collinearity. The final feature set was obtained to differentiate moderate-to-severe anemia. Random forest machine learning was applied and predictive performance was assessed. A decision-tree was obtained to propose a cut-off value of CT Hounsfield units (HU). Results: High correlation with hemoglobin and hematocrit levels was shown for first-order radiomic features (p < 0.001 to p = 0.032). The top 3 features showed high correlation to hemoglobin values (p) and minimal collinearity (r) to the top ranked feature Median (p < 0.001), Energy (p = 0.002, r = 0.387), Minimum (p = 0.032, r = 0.437). Median (p < 0.001) and Minimum (p = 0.003) differed in moderate-to-severe anemia compared to non-anemic state. Median yielded superiority to the combination of Median and Minimum (p(AUC) = 0.015, p(precision) = 0.017, p(accuracy) = 0.612) in the predictive performance employing random forest analysis. A Median HU value ≤ 36.5 indicated moderate-to-severe anemia (accuracy = 0.90, precision = 0.80). Conclusions: First-order radiomic features correlate with hemoglobin levels and may be feasible for the prediction of moderate-to-severe anemia. High dimensional radiomic features did not aid augmenting the data in our exemplary use case of intraluminal blood component assessment.
Using 9.9 fb−1 of e+e− collision data collected by the BESIII detector at center-of-mass energies between 4.15 and 4.30 GeV, we search for the processes e+e−→γX(3872) with X(3872)→π0χc0 and X(3872)→ππχc0. Depending on the fitting model, the statistical significance for X(3872)→π0χc0 ranges from 1.3σ to 2.8σ. We set upper limits (at 90\% C.L.) of B(X(3872)→π0χc0)B(X(3872)→π+π−J/ψ)<3.6, B(X(3872)→π+π−χc0)B(X(3872)→π+π−J/ψ)<0.68, and B(X(3872)→π0π0χc0)B(X(3872)→π+π−J/ψ)<1.7. Combined with the BESIII measurement of X(3872)→π0χc1, we also set an upper limit of B(X(3872)→π0χc0)B(X(3872)→π0χc1)<4.4.
Using 9.9 fb−1 of e+e− collision data collected by the BESIII detector at center-of-mass energies between 4.15 and 4.30 GeV, we search for the processes e+e−→γX(3872) with X(3872)→π0χc0 and X(3872)→ππχc0. Depending on the fitting model, the statistical significance for X(3872)→π0χc0 ranges from 1.3σ to 2.8σ. We set upper limits (at 90\% C.L.) of B(X(3872)→π0χc0)B(X(3872)→π+π−J/ψ)<3.6, B(X(3872)→π+π−χc0)B(X(3872)→π+π−J/ψ)<0.68, and B(X(3872)→π0π0χc0)B(X(3872)→π+π−J/ψ)<1.7. Combined with the BESIII measurement of X(3872)→π0χc1, we also set an upper limit of B(X(3872)→π0χc0)B(X(3872)→π0χc1)<4.4.
Using 9.9 fb−1 of e+e− collision data collected by the BESIII detector at center-of-mass energies between 4.15 and 4.30 GeV, we search for the processes e+e−→γX(3872) with X(3872)→π0χc0 and X(3872)→ππχc0. Depending on the fitting model, the statistical significance for X(3872)→π0χc0 ranges from 1.3σ to 2.8σ. We set upper limits (at 90\% C.L.) of B(X(3872)→π0χc0)B(X(3872)→π+π−J/ψ)<3.6, B(X(3872)→π+π−χc0)B(X(3872)→π+π−J/ψ)<0.68, and B(X(3872)→π0π0χc0)B(X(3872)→π+π−J/ψ)<1.7. Combined with the BESIII measurement of X(3872)→π0χc1, we also set an upper limit of B(X(3872)→π0χc0)B(X(3872)→π0χc1)<4.4.
Objectives: To assess the impact of noise-optimised virtual monoenergetic imaging (VMI+) on image quality and diagnostic evaluation in abdominal dual-energy CT scans with impaired portal-venous contrast.
Methods: We screened 11,746 patients who underwent portal-venous abdominal dual-energy CT for cancer staging between 08/2014 and 11/2019 and identified those with poor portal-venous contrast.
Standard linearly-blended image series and VMI+ image series at 40, 50, and 60 keV were reconstructed. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of abdominal organs and vascular structures were calculated. Image noise, image contrast and overall image quality were rated by three radiologists using 5-point Likert scale.
Results: 452 of 11,746 (4%) exams were poorly opacified. We excluded 190 cases due to incomplete datasets or multiple exams of the same patient with a final study group of 262. Highest CNR values in all abdominal organs (liver, 6.4 ± 3.0; kidney, 17.4 ± 7.5; spleen, 8.0 ± 3.5) and vascular structures (aorta, 16.0 ± 7.3; intrahepatic vein, 11.3 ± 4.7; portal vein, 15.5 ± 6.7) were measured at 40 keV VMI+ with significantly superior values compared to all other series. In subjective analysis, highest image contrast was seen at 40 keV VMI+ (4.8 ± 0.4), whereas overall image quality peaked at 50 keV VMI+ (4.2 ± 0.5) with significantly superior results compared to all other series (p < 0.001).
Conclusions: Image reconstruction using VMI+ algorithm at 50 keV significantly improves image contrast and image quality of originally poorly opacified abdominal CT scans and reduces the number of non-diagnostic scans.
Advances in knowledge: We validated the impact of VMI+ reconstructions in poorly attenuated DECT studies of the abdomen in a big data cohort.
Using 7.33 fb−1 of e+e− collision data collected by the BESIII detector at center-of-mass energies between 4.128 and 4.226~GeV, we observe for the first time the decay D±s→ωπ±η with a statistical significance of 7.6σ. The measured branching fraction of this decay is (0.54±0.12±0.04)%, where the first uncertainty is statistical and the second is systematic.
Highlights
• Assessment of coronary artery plaque burden according to the CAC-DRS Score correlated well with pulmonary involvement of SARS-CoV-2 pneumonia (min. r=0.81, 95% CI 0.76 to 0.86).
• Visual and quantitative CAC-DRS Score of coronary artery plaque burden provided independent prognostic information on all-cause mortality in patients with SARS-CoV-2 pneumonia (p=0.0016 and p<0.0001, respectively).
• Incorporating CAC-DRS Score and pulmonary involvement into clinical decision making revealed great potential to discriminate patients with fatal outcomes from a mild course of disease (AUC 0.938, 95% CI 0.89 to 0.97) and the need for intensive care treatment (AUC 0.801, 95% CI 0.77 to 0.83).
Purpose: To assess and correlate pulmonary involvement and outcome of SARS-CoV-2 pneumonia with the degree of coronary plaque burden based on the CAC-DRS classification (Coronary Artery Calcium Data and Reporting System).
Methods: This retrospective study included 142 patients with confirmed SARS-CoV-2 pneumonia (58 ± 16 years; 57 women) who underwent non-contrast CT between January 2020 and August 2021 and were followed up for 129 ± 72 days. One experienced blinded radiologist analyzed CT series for the presence and extent of calcified plaque burden according to the visual and quantitative HU-based CAC-DRS Score. Pulmonary involvement was automatically evaluated with a dedicated software prototype by another two experienced radiologists and expressed as Opacity Score.
Results: CAC-DRS Scores derived from visual and quantitative image evaluation correlated well with the Opacity Score (r=0.81, 95% CI 0.76-0.86, and r=0.83, 95% CI 0.77-0.89, respectively; p<0.0001) with higher correlation in severe than in mild stage SARS-CoV-2 pneumonia (p<0.0001). Combined, CAC-DRS and Opacity Scores revealed great potential to discriminate fatal outcomes from a mild course of disease (AUC 0.938, 95% CI 0.89-0.97), and the need for intensive care treatment (AUC 0.801, 95% CI 0.77-0.83). Visual and quantitative CAC-DRS Scores provided independent prognostic information on all-cause mortality (p=0.0016 and p<0.0001, respectively), both in univariate and multivariate analysis.
Conclusions: Coronary plaque burden is strongly correlated to pulmonary involvement, adverse outcome, and death due to respiratory failure in patients with SARS-CoV-2 pneumonia, offering great potential to identify individuals at high risk.
Highlights
• MRI and ultrasound provided significant correlations between findings suggestive of vasculitis and the final diagnosis.
• Careful selection of available imaging techniques is warranted considering the time course, location, and clinical history.
• Considering its moderate diagnostic power to distinguish tracer uptake, a holistic view of PET/CT findings is essential.
Abstract
Purpose: To assess the diagnostic value of different imaging modalities in distinguishing systemic vasculitis from other internal and immunological diseases.
Methods: This retrospective study included 134 patients with suspected vasculitis who underwent ultrasound, magnetic resonance imaging (MRI), or 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) between 01/2010 and 01/2019, finally consisting of 70 individuals with vasculitis. The main study parameter was the confirmation of the diagnosis using one of the three different imaging modalities, with the adjudicated clinical and histopathological diagnosis as the gold standard. A secondary parameter was the morphological appearance of the vessel affected by vasculitis.
Results: Patients with systemic vasculitis had myriad clinical manifestations with joint pain as the most common symptom. We found significant correlations between different imaging findings suggestive of vasculitis and the final adjudicated clinical diagnosis. In this context, on MRI, vessel wall thickening, edema, and diameter differed significantly between vasculitis and non-vasculitis groups (p < 0.05). Ultrasound revealed different findings that may serve as red flags in identifying patients with vasculitis, such as vascular occlusion or halo sign (p = 0.02 vs. non-vasculitis group). Interestingly, comparing maximal standardized uptake values from PET/CT examinations with vessel wall thickening or vessel diameter did not result in significant differences (p > 0.05).
Conclusions: We observed significant correlations between different imaging findings suggestive of vasculitis on ultrasound or MRI and the final adjudicated diagnosis. While ultrasound and MRI were considered suitable imaging methods for detecting and discriminating typical vascular changes, 18F-FDG PET/CT requires careful timing and patient selection given its moderate diagnostic accuracy.
Purpose: To assess the diagnostic precision of three different workstations for measuring thoracic aortic aneurysms (TAAs) in vivo and ex vivo using either pre-interventional computed tomography angiography scans (CTA) or a specifically designed phantom model.
Methods: This retrospective study included 23 patients with confirmed TAA on routinely performed CTAs. In addition to phantom tube diameters, one experienced blinded radiologist evaluated the dimensions of TAAs on three different workstations in two separate rounds. Precision was assessed by calculating measurement errors. In addition, correlation analysis was performed using Pearson correlation.
Results: Measurements acquired at the Siemens workstation deviated by 3.54% (range, 2.78–4.03%; p = 0.14) from the true size, those at General Electric by 4.05% (range, 1.46–7.09%; p < 0.0001), and at TeraRecon by 4.86% (range, 3.22–6.45%; p < 0.0001). Accordingly, Siemens provided the most precise workstation at simultaneously most fluctuating values (scattering of 4.46%). TeraRecon had the smallest fluctuation (scattering of 2.83%), but the largest deviation from the true size of the phantom. The workstation from General Electric showed a scattering of 2.94%. The highest overall correlation between the 1st and 2nd rounds was observed with measurements from Siemens (r = 0.898), followed by TeraRecon (r = 0.799), and General Electric (r = 0.703). Repetition of measurements reduced processing times by 40% when using General Electric, by 20% with Siemens, and by 18% with TeraRecon.
Conclusions: In conclusion, all three workstations facilitated precise assessment of dimensions in the majority of cases at simultaneously high reproducibility, ensuring accurate pre-interventional planning of thoracic endovascular aortic repair.