Refine
Year of publication
Document Type
- Article (78) (remove)
Language
- English (78) (remove)
Has Fulltext
- yes (78)
Is part of the Bibliography
- no (78)
Keywords
- Magnetic resonance imaging (7)
- Bone density (4)
- CT (4)
- Computed tomography (4)
- Hepatocellular carcinoma (4)
- MRI (4)
- Osteoporosis (4)
- Artificial intelligence (3)
- Cancer (3)
- Multidetector computed tomography (3)
Institute
- Medizin (78)
- Informatik und Mathematik (3)
- Informatik (1)
- Physik (1)
- Sonderforschungsbereiche / Forschungskollegs (1)
Rationale and Objectives: Bone non-union is a serious complication of distal radius fractures (DRF) that can result in functional limitations and persistent pain. However, no accepted method has been established to identify patients at risk of developing bone non-union yet. This study aimed to compare various CT-derived metrics for bone mineral density (BMD) assessment to identify predictive values for the development of bone non-union.
Materials and Methods: CT images of 192 patients with DRFs who underwent unenhanced dual-energy CT (DECT) of the distal radius between 03/2016 and 12/2020 were retrospectively identified. Available follow-up imaging and medical health records were evaluated to determine the occurrence of bone non-union. DECT-based BMD, trabecular Hounsfield unit (HU), cortical HU and cortical thickness ratio were measured in normalized non-fractured segments of the distal radius.
Results: Patients who developed bone non-union were significantly older (median age 72 years vs. 54 years) and had a significantly lower DECT-based BMD (median 68.1 mg/cm3 vs. 94.6 mg/cm3, p < 0.001). Other metrics (cortical thickness ratio, cortical HU, trabecular HU) showed no significant differences. ROC and PR curve analyses confirmed the highest diagnostic accuracy for DECT-based BMD with an area under the curve (AUC) of 0.83 for the ROC curve and an AUC of 0.46 for the PR curve. In logistic regression models, DECT-based BMD was the sole metric significantly associated with bone non-union.
Conclusion: DECT-derived metrics can accurately predict bone non-union in patients who sustained DRF. The diagnostic performance of DECT-based BMD is superior to that of HU-based metrics and cortical thickness ratio.
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
• Early reconstruction of injured cruciate ligaments improves functional outcomes.
• Modern CT imaging can be used to rapidly identify patients with injury to the cruciate ligaments and streamline therapeutic pathways.
• Dual-energy CT demonstrates superior diagnostic accuracy compared to single-energy CT.
Abstract
Background: This study aimed to evaluate the clinical utility of modern single and dual-energy computed tomography (CT) for assessing the integrity of the cruciate ligaments in patients that sustained acute trauma.
Methods: Patients who underwent single- or dual-energy CT followed by 3 Tesla magnetic resonance imaging (MRI) or knee joint arthroscopy between 01/2016 and 12/2022 were included in this retrospective, monocentric study. Three radiologists specialized in musculoskeletal imaging independently evaluated all CT images for the presence of injury to the cruciate ligaments. An MRI consensus reading of two experienced readers and arthroscopy provided the reference standard. Diagnostic accuracy parameters and area under the receiver operator characteristic curve (AUC) were the primary metrics for diagnostic performance.
Results: CT images of 204 patients (median age, 49 years; IQR 36 – 64; 113 males) were evaluated. Dual-energy CT yielded significantly higher diagnostic accuracy and AUC for the detection of injury to the anterior (94% [240/255] vs 75% [266/357] and 0.89 vs 0.66) and posterior cruciate ligaments (95% [243/255] vs 87% [311/357] and 0.90 vs 0.61) compared to single-energy CT (all parameters, p <.005). Diagnostic confidence and image quality were significantly higher in dual-energy CT compared to single-energy CT (all parameters, p <.005).
Conclusions: Modern dual-energy CT is readily available and can serve as a screening tool for detecting or excluding cruciate ligament injuries in patients with acute trauma. Accurate diagnosis of cruciate ligament injuries is crucial to prevent adverse outcomes, including delayed treatment, chronic instability, or long-term functional limitations.
Background: Dual-energy CT (DECT)-derived bone mineral density (BMD) of the distal radius and other CT-derived metrics related to bone health have been suggested for opportunistic osteoporosis screening and risk evaluation for sustaining distal radius fractures (DRFs).
Methods: The distal radius of patients who underwent DECT between 01/2016 and 08/2021 was retrospectively analyzed. Cortical Hounsfield Unit (HU), trabecular HU, cortical thickness, and DECT-based BMD were acquired from a non-fractured, metaphyseal area in all examinations. Receiver-operating characteristic (ROC) analysis was conducted to determine the area under the curve (AUC) values for predicting DRFs based on DECT-derived BMD, HU values, and cortical thickness. Logistic regression models were then employed to assess the associations of these parameters with the occurrence of DRFs.
Results: In this study, 263 patients (median age: 52 years; interquartile range: 36–64; 132 women; 192 fractures) were included. ROC curve analysis revealed a higher area under the curve (AUC) value for DECT-derived BMD compared to cortical HU, trabecular HU, and cortical thickness (0.91 vs. 0.61, 0.64, and 0.69, respectively; p <.001). Logistic regression models confirmed the association between lower DECT-derived BMD and the occurrence of DRFs (Odds Ratio, 0.83; p <.001); however, no influence was observed for cortical HU, trabecular HU, or cortical thickness.
Conclusions: DECT can be used to assess the BMD of the distal radius without dedicated equipment such as calibration phantoms to increase the detection rates of osteoporosis and stratify the individual risk to sustain DRFs. In contrast, assessing HU-based values and cortical thickness does not provide clinical benefit.
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.
Rationale and objectives: To provide a detailed analysis of injury patterns of the spine following blunt trauma and establish the role of supplementary MRI by evaluating discrepancies in the detection rates of damaged structures in CT and MRI.
Method: 216 patients with blunt trauma to the spine who underwent CT followed by supplementary MRI were included in this study. Two board-certified radiologists blinded to clinical symptoms and injury mechanisms independently interpreted all acquired CT and MRI images. The interpretation was performed using a dedicated catalogue of typical findings associated with spinal trauma and assessed for spinal stability using the AO classification systems.
Results: Lesions to structures associated with spinal instability were present in 31.0% in the cervical spine, 12.3% in the thoracic spine, and 29.9% in the lumbar spine. In all spinal segments, MRI provided additional information regarding potentially unstable injuries. Novel information derived from supplementary MRI changed clinical management in 3.6% of patients with injury to the cervical spine. No change in clinical management resulted from novel information on the thoracolumbar spine. Patients with injuries to the vertebral body, intervertebral disc, or spinous process were significantly more likely to benefit from supplementary MRI.
Conclusion: In patients that sustained blunt spinal trauma, supplementary MRI of the cervical spine should routinely be performed to detect injuries that require surgical treatment, whereas CT is the superior imaging modality for the detection of unstable injuries in the thoracolumbar spine.
Purpose: To stratify differences in visual semantic and quantitative imaging features in intensive care patients with nonspecific mastoid effusions versus patients with acute mastoiditis (AM) requiring surgical treatment. Methods: We included 48 patients (male, 28; female, 20; mean age, 59.5 ± 18.1 years) with mastoid opacification (AM, n = 24; control, n = 24) who underwent clinically indicated cerebral CT between 12/2007 and 07/2018 in this retrospective study. Semantic features described the extend and asymmetry of mastoid and middle-ear cavity opacification and complications like erosive changes. Minimum, maximum and mean Hounsfield unit (HU) values were obtained as quantitative features. We analyzed the features employing univariate testing. Results: Compared to intensive care patients, AM patients revealed asymmetric mastoid or middle-ear cavity opacification (likelihood-ratio (LR) < 0.001). Applying a dedicated threshold of the extent of opacification, AM patients reached significance levels of LR = 0.042 and 0.002 for mastoid and middle-ear cavity opacification. AM cases showed higher maximum and mean HU values (p = 0.009, p = 0.024). Conclusions: We revealed that the extent and asymmetry of mastoid and middle-ear cavity opacification differs significantly between AM patients and intensive care patients. Multicenter research is needed to expand our cohort and possibly pave the way to build a non-invasive predictive model for AM in the future.
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.
Purpose: To identify transjugular intrahepatic portosystemic shunt (TIPS) thrombosis in abdominal CT scans applying quantitative image analysis.
Materials and methods: We retrospectively screened 184 patients to include 20 patients (male, 8; female, 12; mean age, 60.7 ± 8.87 years) with (case, n = 10) and without (control, n = 10) in-TIPS thrombosis who underwent clinically indicated contrast-enhanced and unenhanced abdominal CT followed by conventional TIPS-angiography between 08/2014 and 06/2020. First, images were scored visually. Second, region of interest (ROI) based quantitative measurements of CT attenuation were performed in the inferior vena cava (IVC), portal vein and in four TIPS locations. Minimum, maximum and average Hounsfield unit (HU) values were used as absolute and relative quantitative features. We analyzed the features with univariate testing.
Results: Subjective scores identified in-TIPS thrombosis in contrast-enhanced scans with an accuracy of 0.667 – 0.833. Patients with in-TIPS thrombosis had significantly lower average (p < 0.001), minimum (p < 0.001) and maximum HU (p = 0.043) in contrast-enhanced images. The in-TIPS / IVC ratio in contrast-enhanced images was significantly lower in patients with in-TIPS thrombosis (p < 0.001). No significant differences were found for unenhanced images. Analyzing the visually most suspicious ROI with consecutive calculation of its ratio to the IVC, all patients with a ratio < 1 suffered from in-TIPS thrombosis (p < 0.001, sensitivity and specificity = 100%).
Conclusion: Quantitative analysis of abdominal CT scans facilitates the stratification of in-TIPS thrombosis. In contrast-enhanced scans, an in-TIPS / IVC ratio < 1 could non-invasively stratify all patients with in-TIPS thrombosis.
Rationale and objectives: The objective of this study was to analyze the role of dynamic magnetic resonance imaging (MRI) in patients who suffered from groin pain and whose physical examination and ultrasound returned inconclusive/indefinite results, as well as in patients receiving an ongoing assessment for a previous herniotomy.
Material and methods: For this study, 25 patients 14 women and 11 men were selected with a mean age of 41.6 years, including clinical complaints, such as groin pain and or a previous herniotomies. These patients underwent dynamic MRI. Reports were created by a radiology resident and a radiology consultant. Clinical and ultrasound documentation were compared to with imaging results from the MRI.
Results: The results of the dynamic MRI were negative for 23 patients (92%) and positive for two patients (8%). One patient suffered from an indirect hernia and one from a femoral hernia. A repeated hernia was an excluding for the preoperated patients with pain and ongoing assessment.
Conclusions: Dynamic MRI shows substantially higher diagnostic performance in exclusion of inguinal hernia, when compared to a physical examination and ultrasound. The examination can also be used in assessments to analyze the operation’s results.
Diagnostic value of dynamic magnetic resonance imaging of temporomandibular joint dysfunction
(2021)
Background: To estimate the diagnostic value of dynamic magnetic resonance imaging (MRI) for the assessment of the temporomandibular joint (TMJ) compared to standard static MRI sequences in patients with TMJ dysfunction (TMD).
Methods and materials: This retrospective study included 71 patients with clinical diagnose of TMD. We acquired 5 static T1- and T2-weighted sequences in parasagittal and paracoronal views and one dynamic sequence (trueFISP) in parasagittal view for each TMJ. Image analysis included evaluation of morphology and function of intra-articular structures and rating of the dynamic images as more, equally, or less informative compared to static MRI sequences.
Results: Mean age was 35.0 ± 14.7 years and 50/71 (70.4%) were female. 127/142 (89.4%) TMJs were of diagnostic quality. 42/127 (33.1%) TMJs showed no disc displacement (DD), 56 (44.1%) had DD with disc reduction (DDwR), and 29 (22.8%) had DD without disc reduction (DDwoR). In 38/127 (29.9%) TMJs, dynamic images were rated “more informative”, in 84/127 (66.2%) “equally informative”, and in 5/127 (3.9%) “less informative” compared to solely static images. Overall, 27/71 (38.0%) patients benefited from additional dynamic sequences compared to solely static images. Dynamic images were “more informative” in TMJs with DDwR (23/56 [41.1%], p < 0.001) and in TMJs with DDwoR (13/29 [44.8%], p = 0.007), while it had no beneficial value for TMJ without DD. For evaluation of joint effusion, static T2-weighted images were rated better in 102/127 (80.3%) TMJs compared to dynamic images (<0.001).
Conclusion: Dynamic MRI sequences are beneficial for the evaluation of morphology and function of the TMJ compared to static sequences, especially in patients with temporomandibular disc displacement.
Background: Prostate cancer is a major health concern in aging men. Paralleling an aging society, prostate cancer prevalence increases emphasizing the need for efcient diagnostic algorithms.
Methods: Retrospectively, 106 prostate tissue samples from 48 patients (mean age,
66 ± 6.6 years) were included in the study. Patients sufered from prostate cancer (n = 38) or benign prostatic hyperplasia (n = 10) and were treated with radical prostatectomy or Holmium laser enucleation of the prostate, respectively. We constructed tissue microarrays (TMAs) comprising representative malignant (n = 38) and benign (n = 68) tissue cores. TMAs were processed to histological slides, stained, digitized and assessed for the applicability of machine learning strategies and open–source tools in diagnosis of prostate cancer. We applied the software QuPath to extract features for shape, stain intensity, and texture of TMA cores for three stainings, H&E, ERG, and PIN-4. Three machine learning algorithms, neural network (NN), support vector machines (SVM), and random forest (RF), were trained and cross-validated with 100 Monte Carlo random splits into 70% training set and 30% test set. We determined AUC values for single color channels, with and without optimization of hyperparameters by exhaustive grid search. We applied recursive feature elimination to feature sets of multiple color transforms.
Results: Mean AUC was above 0.80. PIN-4 stainings yielded higher AUC than H&E and
ERG. For PIN-4 with the color transform saturation, NN, RF, and SVM revealed AUC of 0.93 ± 0.04, 0.91 ± 0.06, and 0.92 ± 0.05, respectively. Optimization of hyperparameters improved the AUC only slightly by 0.01. For H&E, feature selection resulted in no increase of AUC but to an increase of 0.02–0.06 for ERG and PIN-4.
Conclusions: Automated pipelines may be able to discriminate with high accuracy between malignant and benign tissue. We found PIN-4 staining best suited for classifcation. Further bioinformatic analysis of larger data sets would be crucial to evaluate the reliability of automated classifcation methods for clinical practice and to evaluate potential discrimination of aggressiveness of cancer to pave the way to automatic precision medicine.
The purpose of this study is to compare the efficacy and safety of microwave ablation (MWA) versus laser-induced thermotherapy (LITT) as a local treatment for hepatocellular carcinoma (HCC,) with regard to therapy response, survival rates, and complication rates as measurable outcomes. This retrospective study included 250 patients (52 females and 198 males; mean age: 66 ± 10 years) with 435 tumors that were treated by MWA and 53 patients (12 females and 41 males; mean age: 67.5 ± 8 years) with 75 tumors that were treated by LITT. Tumor response was evaluated using CEMRI (contrast-enhanced magnetic resonance imaging). Overall, 445 MWA sessions and 76 LITT sessions were performed. The rate of local tumor progression (LTP) and the rate of intrahepatic distant recurrence (IDR) were 6% (15/250) and 46% (115/250) in the MWA-group and 3.8% (2/53) and 64.2% (34/53) in the LITT-group, respectively. The 1-, 3-, and 5-year overall survival (OS) rates calculated from the date of diagnosis were 94.3%, 65.4%, and 49.1% in the MWA-group and 96.2%, 54.7%, and 30.2% in the LITT-group, respectively (p-value: 0.002). The 1-, 2-, and 3-year disease-free survival (DFS) rates were 45.9%, 30.6%, and 24.8% in the MWA-group and 54.7%, 30.2%, and 17% in the LITT-group, respectively (p-value: 0.719). Initial complete ablation rate was 97.7% (425/435) in the MWA-group and 98.7% (74/75) in the LITT-group (p-value > 0.99). The overall complication rate was 2.9% (13/445) in the MWA-group and 7.9% (6/76) in the LITT-group (p-value: 0.045). Based on the results, MWA and LITT thermal ablation techniques are well-tolerated, effective, and safe for the local treatment of HCC. However, MWA is recommended over LITT for the treatment of HCC, since the patients in the MWA-group had higher survival rates.
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).
Our purpose was to analyze the robustness and reproducibility of magnetic resonance imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI acquisition as scan-rescan using a 3 Tesla MRI scanner. We applied T2-weighted (T2w) half-Fourier acquisition single-shot turbo spin-echo (HASTE), T2w turbo spin-echo (TSE), T2w fluid-attenuated inversion recovery (FLAIR), T2 map and T1-weighted (T1w) TSE. Images were resampled to isotropic voxels. Fruits were segmented. The workflow was repeated by a second reader and the first reader after a pause of one month. We applied PyRadiomics to extract 107 radiomic features per fruit and sequence from seven feature classes. We calculated concordance correlation coefficients (CCC) and dynamic range (DR) to obtain measurements of feature robustness. Intraclass correlation coefficient (ICC) was calculated to assess intra- and inter-observer reproducibility. We calculated Gini scores to test the pairwise discriminative power specific for the features and MRI sequences. We depict Bland Altmann plots of features with top discriminative power (Mann–Whitney U test). Shape features were the most robust feature class. T2 map was the most robust imaging technique (robust features (rf), n = 84). HASTE sequence led to the least amount of rf (n = 20). Intra-observer ICC was excellent (≥ 0.75) for nearly all features (max–min; 99.1–97.2%). Deterioration of ICC values was seen in the inter-observer analyses (max–min; 88.7–81.1%). Complete robustness across all sequences was found for 8 features. Shape features and T2 map yielded the highest pairwise discriminative performance. Radiomics validity depends on the MRI sequence and feature class. T2 map seems to be the most promising imaging technique with the highest feature robustness, high intra-/inter-observer reproducibility and most promising discriminative power.
Low serum concentrations of the amino acid homoarginine (HA) are associated with increased cardiovascular mortality by incompletely understood mechanisms. This study sought to assess the influence of HA on cardiac remodeling in rats undergoing either transaortic banding or inhibition of nitric oxide synthesis by Nω-Nitro-L-arginine methyl ester hydrochloride (L-NAME). Male Wistar rats (n = 136) underwent sham operation (SH) or aortic banding (AB). Both groups were equally divided into 14 subgroups, receiving different doses of HA alone or in combination with lisinopril, spironolactone, or L-NAME for 4 weeks. HA treatment in AB animals resulted in a dose-dependent improvement of cardiac function up to a concentration of 800 mg·kg−1·day−1. Combining 800 mg·kg−1·day−1 HA with spironolactone or lisinopril yielded additional effects, showing a positive correlation with LV ejection fraction (+33%, p = 0.0002) and fractional shortening (+41%, p = 0.0014). An inverse association was observed with collagen area fraction (−41%, p < 0.0001), myocyte cross-sectional area (−22%, p < 0.0001) and the molecular markers atrial natriuretic factor (−74%, p = 0.0091), brain natriuretic peptide (−42%, p = 0.0298), beta-myosin heavy chain (−46%, p = 0.0411), and collagen type V alpha 1 chain (−73%, p = 0.0257) compared to placebo-treated AB animals. Co-administration of HA and L-NAME was found to attenuate cardiac remodeling and prevent NO-deficient hypertension following AB. HA treatment has led to a dose-dependent improvement of myocardial function and marked histological and molecular changes in cardiac remodeling following AB. Combining HA with standard heart failure medication resulted in additional beneficial effects boosting its direct impact on heart failure pathophysiology.
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.
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.