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Background: Computed tomography (CT) low-dose (LD) imaging is used to lower radiation exposure, especially in vascular imaging; in current literature, this is mostly on latest generation high-end CT systems.
Purpose: To evaluate the effects of reduced tube current on objective and subjective image quality of a 15-year-old 16-slice CT system for pulmonary angiography (CTPA).
Material and Methods: CTPA scans from 60 prospectively randomized patients (28 men, 32 women) were examined in this study on a 15-year-old 16-slice CT scanner system. Standard CT (SD) settings were 100 kV and 150 mAs, LD settings were 100 kV and 50 mAs. Attenuation of the pulmonary trunk, various anatomic landmarks, and image noise were quantitatively measured; contrast-to-noise ratios (CNR) and signal-to-noise ratios (SNR) were calculated. Three independent blinded radiologists subjectively rated each image series using a 5-point grading scale.
Results: CT dose index (CTDI) in the LD series was 66.46% lower compared to the SD settings (2.49 ± 0.55 mGy versus 7.42 ± 1.17 mGy). Attenuation of the pulmonary trunk showed similar results for both series (SD 409.55 ± 91.04 HU; LD 380.43 HU ± 93.11 HU; P = 0.768). Subjective image analysis showed no significant differences between SD and LD settings regarding the suitability for detection of central and peripheral PE (central SD/LD, 4.88; intra-class correlation coefficients [ICC], 0.894/4.83; ICC, 0.745; peripheral SD/LD, 4.70; ICC, 0.943/4.57; ICC, 0.919; all P > 0.4).
Conclusion: The LD protocol, on a 15-year-old CT scanner system without current high-end hardware or post-processing tools, led to a dose reduction of approximately 67% with similar subjective image quality and delineation of central and peripheral pulmonary arteries.
BACKGROUND: Evaluation of latest generation automated attenuation-based tube potential selection (ATPS) impact on image quality and radiation dose in contrast-enhanced chest-abdomen-pelvis computed tomography examinations for gynaecologic cancer staging.
METHODS: This IRB approved single-centre, observer-blinded retrospective study with a waiver for informed consent included a total of 100 patients with contrast-enhanced chest-abdomen-pelvis CT for gynaecologic cancer staging. All patients were examined with activated ATPS for adaption of tube voltage to body habitus. 50 patients were scanned on a third-generation dual-source CT (DSCT), and another 50 patients on a second-generation DSCT. Predefined image quality setting remained stable between both groups at 120 kV and a current of 210 Reference mAs. Subjective image quality assessment was performed by two blinded readers independently. Attenuation and image noise were measured in several anatomic structures. Signal-to-noise ratio (SNR) was calculated. For the evaluation of radiation exposure, CT dose index (CTDIvol) values were compared.
RESULTS: Diagnostic image quality was obtained in all patients. The median CTDIvol (6.1 mGy, range 3.9-22 mGy) was 40 % lower when using the algorithm compared with the previous ATCM protocol (median 10.2 mGy · cm, range 5.8-22.8 mGy). A reduction in potential to 90 kV occurred in 19 cases, a reduction to 100 kV in 23 patients and a reduction to 110 kV in 3 patients of our experimental cohort. These patients received significantly lower radiation exposure compared to the former used protocol.
CONCLUSION: Latest generation automated ATPS on third-generation DSCT provides good diagnostic image quality in chest-abdomen-pelvis CT while average radiation dose is reduced by 40 % compared to former ATPS protocol on second-generation DSCT.
Background: Various studies have been made about the most effective and safest type of treatment for vertebral compression fractures (VCFs). Long-term results are needed for qualitative evaluation.
Purpose: The purpose of the study is to evaluate the effectiveness of percutaneous vertebroplasty (PVP) and percutaneous kyphoplasty (PKP) procedures for VCFs.
Materials and Methods: Forty-nine patients who received either PVP or PKP between 2002 and 2015 returned a specially developed questionnaire and were included in a cross-sectional outcome analysis. The questionnaire assessed pain development by use of a visual analog scale (VAS). Imaging data (CT scans) were retrospectively analyzed for identification of cement leakage.
Results: Patients’ VAS scores significantly decreased after treatment (7.0 ± 3.4 => 3.7 ± 3.4), (p < 0.001). The average pain reduction in patients treated with PVP was −3.3 ± 3.8 (p < 0.001) (median −3.5) and −4.0 ± 3.9 (p < 0.001) (median −4.5) in patients treated with PKP. Fifteen Patients (41.7%) receiving PVP and four patients (30.7%) receiving PKP experienced recurrence of pain. Cement leakage occurred in 10 patients (22.73%). Patients with cement leakage showed comparable VAS scores after treatment (6.8 ± 3.5 => 1.4 ± 1.6), (p = 0.008). Thirty-nine patients reported an increase in mobility (79.6%) and 41 patients an improvement in quality of life (83.7%).
Conclusion: Pain reduction by means of PVP or PKP in patients with VCFs was discernible over the period of observation. Percutaneous vertebroplasty and PKP contribute to the desired treatment results. However, the level of low pain may not remain constant.
Background: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a novel AI software version for automated BA assessment in comparison to the Greulich-Pyle method.
Methods: Radiographs of 514 patients were analysed in this retrospective study. Total BA was assessed independently by three blinded radiologists applying the GP method and by the AI software. Overall and gender-specific BA assessment results, as well as reading times of both approaches, were compared, while the reference BA was defined by two blinded experienced paediatric radiologists in consensus by application of the Greulich-Pyle method.
Results: Mean absolute deviation (MAD) and root mean square deviation (RSMD) were significantly lower between AI-derived BA and reference BA (MAD 0.34 years, RSMD 0.38 years) than between reader-calculated BA and reference BA (MAD 0.79 years, RSMD 0.89 years; p < 0.001). The correlation between AI-derived BA and reference BA (r = 0.99) was significantly higher than between reader-calculated BA and reference BA (r = 0.90; p < 0.001). No statistical difference was found in reader agreement and correlation analyses regarding gender (p = 0.241). Mean reading times were reduced by 87% using the AI system.
Conclusions: A novel AI software enabled highly accurate automated BA assessment. It may improve efficiency in clinical routine by reducing reading times without compromising the accuracy compared with the Greulich-Pyle method.
Dual-energy CT (DECT) has emerged into clinical routine as an imaging technique with unique postprocessing utilities that improve the evaluation of different body areas. The virtual non-calcium (VNCa) reconstruction algorithm has shown beneficial effects on the depiction of bone marrow pathologies such as bone marrow edema. Its main advantage is the ability to substantially increase the image contrast of structures that are usually covered with calcium mineral, such as calcified vessels or bone marrow, and to depict a large number of traumatic, inflammatory, infiltrative, and degenerative disorders affecting either the spine or the appendicular skeleton. Therefore, VNCa imaging represents another step forward for DECT to image conditions and disorders that usually require the use of more expensive and time-consuming techniques such as magnetic resonance imaging, positron emission tomography/CT, or bone scintigraphy. The aim of this review article is to explain the technical background of VNCa imaging, showcase its applicability in the different body regions, and provide an updated outlook on the clinical impact of this technique, which goes beyond the sole improvement in image quality.
Background: Dual-source dual-energy computed tomography (DECT) offers the potential for opportunistic osteoporosis screening by enabling phantomless bone mineral density (BMD) quantification. This study sought to assess the accuracy and precision of volumetric BMD measurement using dual-source DECT in comparison to quantitative CT (QCT). Methods: A validated spine phantom consisting of three lumbar vertebra equivalents with 50 (L1), 100 (L2), and 200 mg/cm3 (L3) calcium hydroxyapatite (HA) concentrations was scanned employing third-generation dual-source DECT and QCT. While BMD assessment based on QCT required an additional standardised bone density calibration phantom, the DECT technique operated by using a dedicated postprocessing software based on material decomposition without requiring calibration phantoms. Accuracy and precision of both modalities were compared by calculating measurement errors. In addition, correlation and agreement analyses were performed using Pearson correlation, linear regression, and Bland-Altman plots. Results: DECT-derived BMD values differed significantly from those obtained by QCT (p < 0.001) and were found to be closer to true HA concentrations. Relative measurement errors were significantly smaller for DECT in comparison to QCT (L1, 0.94% versus 9.68%; L2, 0.28% versus 5.74%; L3, 0.24% versus 3.67%, respectively). DECT demonstrated better BMD measurement repeatability compared to QCT (coefficient of variance < 4.29% for DECT, < 6.74% for QCT). Both methods correlated well to each other (r = 0.9993; 95% confidence interval 0.9984–0.9997; p < 0.001) and revealed substantial agreement in Bland-Altman plots. Conclusions: Phantomless dual-source DECT-based BMD assessment of lumbar vertebra equivalents using material decomposition showed higher diagnostic accuracy compared to QCT.
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.
Objectives: To analyze the performance of radiological assessment categories and quantitative computational analysis of apparent diffusion coefficient (ADC) maps using variant machine learning algorithms to differentiate clinically significant versus insignificant prostate cancer (PCa). Methods: Retrospectively, 73 patients were included in the study. The patients (mean age, 66.3 ± 7.6 years) were examined with multiparametric MRI (mpMRI) prior to radical prostatectomy (n = 33) or targeted biopsy (n = 40). The index lesion was annotated in MRI ADC and the equivalent histologic slides according to the highest Gleason Grade Group (GrG). Volumes of interest (VOIs) were determined for each lesion and normal-appearing peripheral zone. VOIs were processed by radiomic analysis. For the classification of lesions according to their clinical significance (GrG ≥ 3), principal component (PC) analysis, univariate analysis (UA) with consecutive support vector machines, neural networks, and random forest analysis were performed. Results: PC analysis discriminated between benign and malignant prostate tissue. PC evaluation yielded no stratification of PCa lesions according to their clinical significance, but UA revealed differences in clinical assessment categories and radiomic features. We trained three classification models with fifteen feature subsets. We identified a subset of shape features which improved the diagnostic accuracy of the clinical assessment categories (maximum increase in diagnostic accuracy ΔAUC = + 0.05, p < 0.001) while also identifying combinations of features and models which reduced overall accuracy. Conclusions: The impact of radiomic features to differentiate PCa lesions according to their clinical significance remains controversial. It depends on feature selection and the employed machine learning algorithms. It can result in improvement or reduction of diagnostic performance.
Background: This prospective randomized trial is designed to compare the performance of conventional transarterial chemoembolization (cTACE) using Lipiodol-only with additional use of degradable starch microspheres (DSM) for hepatocellular carcinoma (HCC) in BCLC-stage-B based on metric tumor response. Methods: Sixty-one patients (44 men; 17 women; range 44–85) with HCC were evaluated in this IRB-approved HIPPA compliant study. The treatment protocol included three TACE-sessions in 4-week intervals, in all cases with Mitomycin C as a chemotherapeutic agent. Multiparametric magnetic resonance imaging (MRI) was performed prior to the first and 4 weeks after the last TACE. Two treatment groups were determined using a randomization sheet: In 30 patients, TACE was performed using Lipiodol only (group 1). In 31 cases Lipiodol was combined with DSMs (group 2). Response according to tumor volume, diameter, mRECIST criteria, and the development of necrotic areas were analyzed and compared using the Mann–Whitney-U, Kruskal–Wallis-H-test, and Spearman-Rho. Survival data were analyzed using the Kaplan–Meier estimator. Results: A mean overall tumor volume reduction of 21.45% (± 62.34%) was observed with an average tumor volume reduction of 19.95% in group 1 vs. 22.95% in group 2 (p = 0.653). Mean diameter reduction was measured with 6.26% (± 34.75%), for group 1 with 11.86% vs. 4.06% in group 2 (p = 0.678). Regarding mRECIST criteria, group 1 versus group 2 showed complete response in 0 versus 3 cases, partial response in 2 versus 7 cases, stable disease in 21 versus 17 cases, and progressive disease in 3 versus 1 cases (p = 0.010). Estimated overall survival was in mean 33.4 months (95% CI 25.5–41.4) for cTACE with Lipiosol plus DSM, and 32.5 months (95% CI 26.6–38.4), for cTACE with Lipiodol-only (p = 0.844), respectively. Conclusions: The additional application of DSM during cTACE showed a significant benefit in tumor response according to mRECIST compared to cTACE with Lipiodol-only. No benefit in survival time was observed.
Myocardial fibrosis and inflammation by CMR predict cardiovascular outcome in people living with HIV
(2021)
Objectives_: The goal of this study was to examine prognostic relationships between cardiac imaging measures and cardiovascular outcome in people living with human immunodeficiency virus (HIV) (PLWH) on highly active antiretroviral therapy (HAART).
Background: PLWH have a higher prevalence of cardiovascular disease and heart failure (HF) compared with the noninfected population. The pathophysiological drivers of myocardial dysfunction and worse cardiovascular outcome in HIV remain poorly understood.
Methods: This prospective observational longitudinal study included consecutive PLWH on long-term HAART undergoing cardiac magnetic resonance (CMR) examination for assessment of myocardial volumes and function, T1 and T2 mapping, perfusion, and scar. Time-to-event analysis was performed from the index CMR examination to the first single event per patient. The primary endpoint was an adjudicated adverse cardiovascular event (cardiovascular mortality, nonfatal acute coronary syndrome, an appropriate device discharge, or a documented HF hospitalization).
Results: A total of 156 participants (62% male; age [median, interquartile range]: 50 years [42 to 57 years]) were included. During a median follow-up of 13 months (9 to 19 months), 24 events were observed (4 HF deaths, 1 sudden cardiac death, 2 nonfatal acute myocardial infarction, 1 appropriate device discharge, and 16 HF hospitalizations). Patients with events had higher native T1 (median [interquartile range]: 1,149 ms [1,115 to 1,163 ms] vs. 1,110 ms [1,075 to 1,138 ms]); native T2 (40 ms [38 to 41 ms] vs. 37 ms [36 to 39 ms]); left ventricular (LV) mass index (65 g/m2 [49 to 77 g/m2] vs. 57 g/m2 [49 to 64 g/m2]), and N-terminal pro–B-type natriuretic peptide (109 pg/l [25 to 337 pg/l] vs. 48 pg/l [23 to 82 pg/l]) (all p < 0.05). In multivariable analyses, native T1 was independently predictive of adverse events (chi-square test, 15.9; p < 0.001; native T1 [10 ms] hazard ratio [95% confidence interval]: 1.20 [1.08 to 1.33]; p = 0.001), followed by a model that also included LV mass (chi-square test, 17.1; p < 0.001). Traditional cardiovascular risk scores were not predictive of the adverse events.
Conclusions: Our findings reveal important prognostic associations of diffuse myocardial fibrosis and LV remodeling in PLWH. These results may support development of personalized approaches to screening and early intervention to reduce the burden of HF in PLWH (International T1 Multicenter Outcome Study; NCT03749343).