CXCL1 and CXCL6 Are Potential Predictors for HCC Response to TACE

Distinct immune patterns of hepatocellular carcinoma (HCC) may have prognostic implications in the response to transarterial chemoembolization (TACE). Thus, we aimed to exploratively analyze tumor tissue of HCC patients who do or do not respond to TACE, and to identify novel prognostic biomarkers predictive of response to TACE. We retrospectively included 15 HCC patients who had three consecutive TACE between January 2019 and November 2019. Eight patients had a response while seven patients had no response to TACE. All patients had measurable disease according to mRECIST. Corresponding tumor tissue samples were processed for differential expression profiling using NanoString nCounter^® PanCancer immune profiling panel. Immune-related pathways were broadly upregulated in TACE responders. The top differentially regulated genes were the upregulated CXCL1 (log2fc 4.98, Benjamini-Hochberg (BH)-p < 0.001), CXCL6 (log2fc 4.43, BH-p = 0.016) and the downregulated MME (log2fc -4.33, BH-p 0.001). CD8/T-regs was highly increased in responders, whereas the relative number of T-regs to tumor-infiltrating lymphocytes (TIL) was highly decreased. We preliminary identified CXCL1 and CXCL6 as candidate genes that might have the potential to serve as therapeutically relevant biomarkers in HCC patients. This might pave the way to improve patient selection for TACE in HCC patients beyond expert consensus.

MR angiography facilitates the differentiation of aneurysmal from unicameral bone cysts

OBJECTIVES

The objective of this work was to evaluate the incremental value of MR angiography over plain radiographs and MRI for the differentiation of aneurysmal bone cysts (ABCs) from unicameral bone cysts (UBCs).

METHODS

Thirty-six juvenile patients with histologically secured primary ABCs or UBCs were included in this retrospective study. Two radiologists assessed all obtained images in a blinded fashion using a catalog of previously suggested imaging findings. A second readout with supplementary MR angiography images was performed after 8 weeks to prevent observer recall bias. Diagnostic accuracy parameters were calculated for individual imaging findings, and overall diagnostic accuracy and diagnostic confidence were assessed for all readouts. Receiver operating characteristic (ROC) curve comparison was used to determine the incremental value of MR angiography.

RESULTS

Of 16 imaging features, only abnormal vascularization in MR angiography provided sufficient diagnostic accuracy for the identification of ABCs. Other imaging features such as fluid-fluid levels and internal septations were insufficient for the differentiation of UBCs from ABCs. Availability of MR angiography images significantly increased diagnostic accuracy (94.4 vs 75.0% and 83.3 vs 69.4%, respectively, p < 0.05) and diagnostic confidence (4.5 vs 3.7, p < 0.05) of reading radiologists.

CONCLUSION

The presence of arterial feeders in MR angiography can accurately discriminate primary ABCs from UBCs and increases the diagnostic accuracy and diagnostic confidence of reporting radiologists.

ADVANCES IN KNOWLEDGE

Radiographic differentiation of cystic bone lesions such as ABCs and UBCs remains challenging. We demonstrate that MR angiography provides incremental value and suggest inclusion in standard examination protocols.

Free-breathing accelerated whole-body MRI using an automated workflow: Comparison with conventional breath-hold sequences

Whole-body magnetic resonance imaging (MRI) has become increasingly popular in oncology. However, the long acquisition time might hamper its widespread application. We sought to assess and compare free-breathing sequences with conventional breath-hold examinations in whole-body MRI using an automated workflow process. This prospective study consisted of 20 volunteers and six patients with a variety of pathologies who had undergone whole-body 1.5-T MRI that included T1-weighted radial and Dixon volumetric interpolated breath-hold examination sequences. Free-breathing sequences were operated by using an automated user interface. Image quality, diagnostic confidence, and image noise were evaluated by two experienced radiologists. Additionally, signal-to-noise ratio was measured. Diagnostic performance for the overall detection of pathologies was assessed using the area under the receiver operating characteristics curve (AUC). Study participants were asked to rate their examination experiences in a satisfaction survey. MR free-breathing scans were rated as at least equivalent to conventional MR scans in more than 92% of cases, showing high overall diagnostic accuracy (95% [95% CI 92-100]) and performance (AUC 0.971, 95% CI 0.942-0.988; p < 0.0001) for the assessment of pathologies at simultaneously reduced examination times (25 ± 2 vs. 32 ± 3 min; p < 0.0001). Interrater agreement was excellent for both free-breathing (ϰ = 0.96 [95% CI 0.88-1.00]) and conventional scans (ϰ = 0.93 [95% CI 0.84-1.00]). Qualitative and quantitative assessment for image quality, image noise, and diagnostic confidence did not differ between the two types of MR image acquisition (all p > 0.05). Scores for patient satisfaction were significantly better for free-breathing compared with breath-hold examinations (p = 0.0145), including significant correlations for the grade of noise (r = 0.79, p < 0.0001), tightness (r = 0.71, p < 0.0001), and physical fatigue (r = 0.52, p = 0.0065). In summary, free-breathing whole-body MRI in tandem with an automated user interface yielded similar diagnostic performance at equivalent image quality and shorter acquisition times compared to conventional breath-hold sequences.

Computed Tomography Radiomics to Differentiate Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma

AIMS

Intrahepatic cholangiocarcinoma (iCCA) and hepatocellular carcinoma (HCC) differ in prognosis and treatment. We aimed to non-invasively differentiate iCCA and HCC by means of radiomics extracted from contrast-enhanced standard-of-care computed tomography (CT).

MATERIALS AND METHODS

In total, 94 patients (male, n = 68, mean age 63.3 ± 12.4 years) with histologically confirmed iCCA (n = 47) or HCC (n = 47) who underwent contrast-enhanced abdominal CT between August 2014 and November 2021 were retrospectively included. The enhancing tumour border was manually segmented in a clinically feasible way by defining three three-dimensional volumes of interest per tumour. Radiomics features were extracted. Intraclass correlation analysis and Pearson metrics were used to stratify robust and non-redundant features with further feature reduction by LASSO (least absolute shrinkage and selection operator). Independent training and testing datasets were used to build four different machine learning models. Performance metrics and feature importance values were computed to increase the models' interpretability.

RESULTS

The patient population was split into 65 patients for training (iCCA, n = 32) and 29 patients for testing (iCCA, n = 15). A final combined feature set of three radiomics features and the clinical features age and sex revealed a top test model performance of receiver operating characteristic (ROC) area under the curve (AUC) = 0.82 (95% confidence interval =0.66-0.98; train ROC AUC = 0.82) using a logistic regression classifier. The model was well calibrated, and the Youden J Index suggested an optimal cut-off of 0.501 to discriminate between iCCA and HCC with a sensitivity of 0.733 and a specificity of 0.857.

CONCLUSIONS

Radiomics-based imaging biomarkers can potentially help to non-invasively discriminate between iCCA and HCC.

CT-radiomics and clinical risk scores for response and overall survival prognostication in TACE HCC patients

We aimed to identify hepatocellular carcinoma (HCC) patients who will respond to repetitive transarterial chemoembolization (TACE) to improve the treatment algorithm. Retrospectively, 61 patients (mean age, 65.3 years ± 10.0 [SD]; 49 men) with 94 HCC mRECIST target-lesions who had three consecutive TACE between 01/2012 and 01/2020 were included. Robust and non-redundant radiomics features were extracted from the 24 h post-embolization CT. Five different clinical TACE-scores were assessed. Seven different feature selection methods and machine learning models were used. Radiomics, clinical and combined models were built to predict response to TACE on a lesion-wise and patient-wise level as well as its impact on overall-survival prognostication. 29 target-lesions of 19 patients were evaluated in the test set. Response rates were 37.9% (11/29) on the lesion-level and 42.1% (8/19) on the patient-level. Radiomics top lesion-wise response prognostications was AUC 0.55-0.67. Clinical scores revealed top AUCs of 0.65-0.69. The best working model combined the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical score mHAP_II_score_group with AUC = 0.70, accuracy = 0.72. We transferred this model on a patient-level to achieve AUC = 0.62, CI = 0.41-0.83. The two radiomics-clinical features revealed overall-survival prognostication of C-index = 0.67. In conclusion, a random forest model using the radiomic feature LargeDependenceHighGrayLevelEmphasis and the clinical mHAP-II-score-group seems promising for TACE response prognostication.

Reduction of radiation dose using real-time visual feedback dosimetry during angiographic interventions

This prospective study sought to evaluate potential savings of radiation dose to medical staff using real-time dosimetry coupled with visual radiation dose feedback during angiographic interventions. For this purpose, we analyzed a total of 214 angiographic examinations that consisted of chemoembolizations and several other types of therapeutic interventions. The Unfors RaySafe i2 dosimeter was worn by the interventionalist at chest height over the lead protection. A total of 110 interventions were performed with real-time radiation dosimetry allowing the interventionalist to react upon higher x-ray exposure and 104 examinations served as the comparative group without real-time radiation monitoring. By using the real-time display during interventions, the overall mean operator radiation dose decreased from 3.67 (IQR, 0.95-23.01) to 2.36 μSv (IQR, 0.52-12.66) (-36%; p = 0.032) at simultaneously reduced operator exposure time by 4.5 min (p = 0.071). Dividing interventions into chemoembolizations and other types of therapeutic interventions, radiation dose decreased from 1.31 (IQR, 0.46-3.62) to 0.95 μSv (IQR, 0.53-3.11) and from 24.39 (IQR, 12.14-63.0) to 10.37 μSv (IQR, 0.85-36.84), respectively, using live-screen dosimetry (p ≤ 0.005). Radiation dose reductions were also observed for the participating assistants, indicating that they could also benefit from real-time visual feedback dosimetry during interventions (-30%; p = 0.039). Integration of real-time dosimetry into clinical processes might be useful in reducing occupational radiation exposure time during angiographic interventions. The real-time visual feedback raised the awareness of interventionalists and their assistants to the potential danger of prolonged radiation exposure leading to the adoption of radiation-sparing practices. Therefore, it might create a safer environment for the medical staff by keeping the applied radiation exposure as low as possible.

Homoarginine in the cardiovascular system: Pathophysiology and recent developments

Upcoming experimental and epidemiological data have identified the endogenous non-proteinogenic amino acid L-homoarginine (L-hArg) not only as a novel biomarker for cardiovascular disease but also as being directly involved in the pathogenesis of cardiac dysfunction. The association of low L-hArg levels with adverse cardiovascular events and mortality has proposed the idea of nutritional supplementation to rescue pathways inversely associated with cardiovascular health. Subsequent clinical and experimental studies contributed significantly to our knowledge of potential effects on the cardiorenal axis, acting either as a biomarker or a cardiovascular active agent. In this review article, we provide a comprehensive summary of the L-hArg metabolism, pathophysiological aspects, and current developments in the field of experimental and clinical evidence in favor of protective cardiovascular effects. Establishing a reliable biomarker to identify patients at high risk to die of cardiovascular disease represents one of the main goals for tackling this disease and providing individual therapeutic guidance.

Imaging biomarkers to stratify lymph node metastases in abdominal CT - Is radiomics superior to dual-energy material decomposition?

Purpose

To assess the potential of radiomic features in comparison to dual-energy CT (DECT) material decomposition to objectively stratify abdominal lymph node metastases.

Materials and methods

In this retrospective study, we included 81 patients (m, 57; median age, 65 (interquartile range, 58.7-73.3) years) with either lymph node metastases (n = 36) or benign lymph nodes (n = 45) who underwent contrast-enhanced abdominal DECT between 06/2015-07/2019. All malignant lymph nodes were classified as unequivocal according to RECIST criteria and confirmed by histopathology, PET-CT or follow-up imaging. Three investigators segmented lymph nodes to extract DECT and radiomics features. Intra-class correlation analysis was applied to stratify a robust feature subset with further feature reduction by Pearson correlation analysis and LASSO. Independent training and testing datasets were applied on four different machine learning models. We calculated the performance metrics and permutation-based feature importance values to increase interpretability of the models. DeLong test was used to compare the top performing models.

Results

Distance matrices and t-SNE plots revealed clearer clusters using a combination of DECT and radiomic features compared to DECT features only. Feature reduction by LASSO excluded all DECT features of the combined feature cohort. The top performing radiomic features model (AUC = 1.000; F1 = 1.000; precision = 1.000; Random Forest) was significantly superior to the top performing DECT features model (AUC = 0.942; F1 = 0.762; precision = 0.800; Stochastic Gradient Boosting) (DeLong < 0.001).

Conclusion

Imaging biomarkers have the potential to stratify unequivocal lymph node metastases. Radiomics models were superior to DECT material decomposition and may serve as a support tool to facilitate stratification of abdominal lymph node metastases.

Dual-energy CT based material decomposition to differentiate intrahepatic cholangiocarcinoma from hepatocellular carcinoma

PURPOSE

To assess the potential of material decomposition in dual-energy CT (DECT) to differentiate intrahepatic cholangiocarcinoma (iCCA) from hepatocellular carcinoma (HCC).

METHOD

In this retrospective study, we included 94 patients (26 female (27.7 %), median age 64.5 (interquartile range 55.5-74.5) years) with either iCCA or HCC who underwent abdominal contrast-enhanced DECT in arterial phase. To test for differences between iCCA (n = 47) and HCC (n = 47), we evaluated mean attenuation and DECT material density values including iodine density (ID), normalized iodine uptake (NIU), fat fraction, and lesion-to-liver parenchyma ratio. Histopathology served as reference standard for all lesions. We used univariate logistic regression models for the outcome iCCA versus HCC. ROC curve analysis was applied to assess discriminative ability of the model. Model accuracy was evaluated by calculating the Brier score. Youden index was applied to establish thresholds to differentiate between iCCA and HCC.

RESULTS

Comparison of quantitative image parameters revealed significant differences between iCCA and HCC for ID (1.6 ± 0.5 mg/ml vs 2.8 ± 0.8 mg/ml, p < 0.001), NIU (14.5 ± 4.8 vs 24.8 ± 10.3, p < 0.001), attenuation (41.9 ± 10.1 HU vs 47.9 ± 8.9 HU, p = 0.003), and fat fraction (12.0 ± 7.8 % vs 9.0 ± 6.4 %, p = 0.045). ROC curve analysis revealed highest ability to differentiate iCCA from HCC for ID (AUC = 0.93, 95 % CI 0.89-0.98). For ID, an optimal threshold of 2.33 mg/dl was determined to discriminate between iCCA and HCC (sensitivity 89.4 %, specificity 76.6 %).

CONCLUSIONS

DECT-based iodine quantification can serve as a tool for the differentiation of iCCA and HCC in contrast-enhanced CT. ID yielded the highest diagnostic performance and may assist in clinical routine CT diagnostics.

Systematic evaluation of imaging techniques and baseline characteristics in patients with suspected vasculitis

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.

Comprehensive comparison of three different workstations for accurate planning of endovascular stent implantation in patients with thoracic aortic aneurysms

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.

•

Pre-interventional planning of TEVAR in patients with TAAs using CTA is feasible.

•

All three workstations facilitated accurate measurements in vivo and ex vivo.

•

Repetition of measurements resulted in faster processing due to learning effects.

Lung Opacity and Coronary Artery Calcium Score: A Combined Tool for Risk Stratification and Outcome Prediction in COVID-19 Patients

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.

Salvaging low contrast abdominal CT studies using noise-optimised virtual monoenergetic image reconstruction

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.

Diagnostic performance and predictive value of D-dimer testing in patients referred to the emergency department for suspected myocardial infarction

PURPOSE

The study sought to assess the performance of D-dimer testing for the diagnosis of acute coronary syndrome (ACS) and prediction of outcomes in patients admitted for suspected myocardial infarction (MI).

RESULTS

A total of 3,557 patients with suspected ACS presenting to a single center with a broad range of symptoms including atypical chest pain were retrospectively recruited between 02/2012-01/2019. Of the study cohort, 435 patients had unstable angina (UA), 420 non-ST-segment elevation myocardial infarction (NSTEMI), 22 ST-segment elevation myocardial infarction (STEMI), and 2,680 non-coronary chest pain. Plasma D-dimer concentrations in patients with hs-cTnT >14 ng/L differed significantly from those with hs-cTnT <14 ng/L (1.5 ± 3.6 mg/L vs. 0.5 ± 0.8 mg/L; p<0.0001). Positive predictive value for a final diagnosis of ACS increased proportionally to rising D-dimer concentrations. The area under the curve (AUC) to discriminate STEMI from non-coronary chest pain (AUC 0.729, 95% confidence interval [CI] 0.71-0.75) was moderate and differed not significantly to UA (AUC 0.595, 95% CI 0.58-0.61; p=0.0653). During a median follow-up of 29 months, higher D-dimer was associated with a significantly increased risk of recurrent MI (quartile 4 vs. 1: hazard ratio [HR], 6.9 [95% CI 1.2-39.9]; p<0.0001) and higher all-cause mortality (HR, 17.4 [95% CI 4.3-69.9]; p<0.0001). D-dimer was an independent predictor of all-cause mortality (p<0.0001) and subsequent MI events (p=0.0333).

CONCLUSIONS

D-dimer testing revealed great potential to provide independent prognostic information on recurrent MI and all-cause mortality. However, D-dimers do not improve the diagnostic performance except if values exceed the 95^th percentile.

Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans

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.

Trial registration Retrospectively registered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-021-00654-9.

Quantification of COVID-19 Opacities on Chest CT - Evaluation of a Fully Automatic AI-approach to Noninvasively Differentiate Critical Versus Noncritical Patients

Objectives

To evaluate the potential of a fully automatic artificial intelligence (AI)-driven computed tomography (CT) software prototype to quantify severity of COVID-19 infection on chest CT in relationship with clinical and laboratory data.

Methods

We retrospectively analyzed 50 patients with laboratory confirmed COVID-19 infection who had received chest CT between March and July 2020. Pulmonary opacifications were automatically evaluated by an AI-driven software and correlated with clinical and laboratory parameters using Spearman-Rho and linear regression analysis. We divided the patients into sub cohorts with or without necessity of intensive care unit (ICU) treatment. Sub cohort differences were evaluated employing Wilcoxon-Mann-Whitney-Test.

Results

We included 50 CT examinations (mean age, 57.24 years), of whom 24 (48%) had an ICU stay. Extent of COVID-19 like opacities on chest CT showed correlations (all p < 0.001 if not otherwise stated) with occurrence of ICU stay (R = 0.74), length of ICU stay (R = 0.81), lethal outcome (R = 0.56) and length of hospital stay (R = 0.33, p < 0.05). The opacities extent was correlated with laboratory parameters: neutrophil count (NEU) (R = 0.60), lactate dehydrogenase (LDH) (R = 0.60), troponin (TNTHS) (R = 0.55) and c-reactive protein (CRP) (R = 0.51). Differences (p < 0.001) between ICU group and non-ICU group concerned longer length of hospital stay (24.04 vs. 10.92 days), higher opacity score (12.50 vs. 4.96) and severity of laboratory data changes such as c-reactive protein (11.64 vs. 5.07 mg/dl, p < 0.01).

Conclusions

Automatically AI-driven quantification of opacities on chest CT correlates with laboratory and clinical data in patients with confirmed COVID-19 infection and may serve as non-invasive predictive marker for clinical course of COVID-19.

Differences in mastoid and middle-ear cavity opacification in CT between intensive care patients and patients with acute mastoiditis requiring surgical treatment

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.

Prevalence of TB/ HIV co-infection in Iran: a systematic review and meta-analysis

INTRODUCTION

Co-infection of TB/ HIV is an emerging threat to a global public health. Although several studies have investigated the prevalence of TB/HIV co-infection in Iran, the results are inconsistent. The current systematic review and meta-analysis was planned to estimate the overall prevalence of TB/HIV co-infection in Iran.

METHODS

Electronic databases, including MEDLINE (via PubMed), SCOPUS, SID and Mag Iran (two Persian scientific search engines) were searched up to 27 Apr 2017. The random effect model was used for estimating the prevalence of TB/ HIV co-infection. Heterogeneity was assessed by subgroup analysis.

RESULTS

Forty-eight articles met our inclusion criteria, with a total of 21,388 individuals. The meta-analysis demonstrates that the prevalence of TB/ HIV co-infection in Iran was 14% [95% confidence interval CI:12-15%]. According to the meta-analysis of 5 subgroups, the prevalence of TB/ HIV co-infection in the subgroup with high intravenous drug users (IVDU) [27%, 95% CI: 20-35%], in border provinces of Iran [17%, 95% CI: 13-21%], in the subgroup with pulmonary tuberculosis (PTB) ≥ 20% [22%, 95% CI: 17-27%], in patients <40 years of age [25%, 95 CI: 19-31%] was significantly higher. There were no significant differences between the prevalence of co-infection among low and high-quality studies. Pulmonary TB was the predominant type of TB among co-infected patients [77%, 95% CI: 71 to 84%].

CONCLUSIONS

Our study demonstrates that the overall prevalence of TB/HIV co-infection in Iran was 14% [95% CI: 12-15%], which was a high rate. Some factors such as using intravenous drugs, living in border provinces of Iran, having PTB, and age <40 years had an impact on the prevalence of co-infection. Results revealed the need of HIV surveillance program among TB patients and screening of HIV-positive patients for diagnosis and treatment of TB. Further large-scale studies about the prevalence of this infection in all provinces of Iran are needed.

Antimicrobial-resistance pattern of Shigella species in children: a six-year study in an Iranian referral Hospital

BACKGROUND

Shigella species are a frequent cause of shigellosis and shigellosis is considered as one of the most common causes of diarrhea in children. This disease is endemic in many developing countries such as Iran. This study was carried out to determine the prevalence and pattern of antimicrobial resistance of Shigella species among pediatric patients with acute diarrhea in Children Medical Center (CMC) Hospital, with a diagnosis of acute diarrhea to CMC Hospital from March 2011 through March 2016. Isolation and identification techniques, as well as the susceptibility tests are described in detail.

RESULTS

Of the 46,795 stool specimens that were sent to the microbiology laboratory of the CMC Hospital for culture and susceptibility testing, 573 (1.2%) were positive for Shigella species. The most common species of Shigella were S. sonnei (n= 335, 58.4%) and S. flexneri (n=229, 40%), followed by S. boydii (n=8, 1.4%) and S. dysenteriae (n=1, 0.2%). S. flexneri was most sensitive to gentamicin (n=17/19, 89%) and amikacin (n=15/18, 83%), while high frequency of resistance to trimethoprim- sulfamethoxazole (n=204/224, 91%) and ampicillin (n=216/228, 95%) was seen. S. boydii was most sensitive to ampicillin (n=5 out of 7, 71%) and cefotaxime (n=6/7, 86%) and the high frequency of resistance was seen against trimethoprim-sulfamethoxazole (n=5/7, 71%). For S. sonnei, the highest sensitivity was reported against amikacin and gentamicin (87% and 80%, respectively), while the highest resistance to trimethoprim- sulfamethoxazole (n=325/331, 98%) and ciprofloxacin (n= 66 out of 76, 87%) was reported. Ciprofloxacin was examined on 115 out of 573 isolates and 84 isolates were resistant (73%). Multidrug-resistance (MDR), (i.e. resistance to three or more classes of antimicrobial agents) was classified into 11 distinct patterns.

CONCLUSIONS

In this study, S. sonnei was the predominant Shigella species. High frequency of resistance to common antimicrobials such as trimethoprim-sulfamethoxazole and ampicillin limits the empirical therapy for the management of shigellosis in Iran. On the other hand, it should be noted that third-generation cephalosporins can be convenient replacing drugs.

Atypical and novel presentations of Coronavirus Disease 2019: a case series of three children

Typical presentations of Coronavirus Disease 2019 (Covid-19) including respiratory symptoms (cough, respiratory distress and hypoxia), fever and dyspnoea are considered main symptoms in adults, but atypical presentation in children could be a diagnostic challenge. We report three children whose initial presentation was gastrointestinal, and in whom Covid-19 infection was found, concluding that cases of acute appendicitis, mesenteric adenitis and flank tenderness may mask an infection with this virus, and should therefore be investigated.

Molecular characteristics and antibiotic resistance profiles of Escherichia coli strains isolated from urinary tract infections in children admitted to children's referral hospital of Qom, Iran

BACKGROUND

Urinary tract infections (UTIs) are a highly prevalent infection among children and Escherichia coli is one of the most important pathogens causing pediatric UTIs. Production of extended spectrum b-lactamase (ESBL) enzymes is an important factor in the emergence of antibiotic resistance among these bacteria. This study aimed to determine the resistance patterns, the frequency of ESBL-encoding genes and the genetic diversity of E. coli strains isolated from children with UTIs who were admitted to children's referral hospital of Hazrat Masoumeh, Qom, Iran.

METHODS

A total of 102 consecutive non-duplicative strains of E.coli that were isolated from children with UTIs were included into the study. Antibiotic susceptibility of the isolates was determined by disk diffusion method according to the CLSI guidelines. The ability of the isolates to produce ESBLs was phenotypically determined by both combined disk test and double disk synergy test. The ESBL encoding genes (bla CTX-M, bla SHV, and bla TEM) in phenotypically confirmed ESBL-positive isolates was detected by PCR method. The genetic relatedness of the isolates was designated by enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR).

RESULTS

Eighty-three percent (n=85) of the children were female. Most of the infected boys (88%, n=15) were less than 1 year of age and most of the infected girls (48%, n=41) aged 1 to 6 years old. The highest sensitivity was observed to nitrofurantoin (8%, n=8), followed by amikacin (12%, n=12) and piperacillin-tazobactam (17%, n=17). In contrast, the highest resistance rate was seen to ampicillin (94%, n=96) and cefazolin (93%, n=95). Eighty-eight percent (90 out of 102) of the strains were multidrug-resistant (MDR). Fifty-eight percent (n=59) of the strains were ESBL-positive and results of the combined disk test was in concordance with PCR. The blaCTX-M was the most frequent ESBL encoding gene (88%, n=52), followed by blaTEM (54%, n=32), and blaSHV (15%, n=9). Based on the ERIC-PCR technique, isolates were clustered in 13 different types. There was no relationship between different ERIC types and origin of the isolates (i.e. hospitalized or outpatients), ESBL-producing ability, and antibiotic resistance patterns.

CONCLUSIONS

High prevalence of ESBL-positive isolates of E. coli (58%) was found in our study and all of them were MDR. In addition, there were statistically significant differences in the resistance rates of ESBL-producers, and non-producers to some antibiotics, which result in limiting their therapeutic options. Continuous surveillance of the emergence of ESBL-producing isolates and their antibiotic resistance profiles as well as using appropriate typing methods is needed for reducing their spread, selecting appropriate treatment regimens and finding hospital outbreaks.

Comparative in vitro activities of seven antifungal drugs against clinical isolates of Candida parapsilosis complex

OBJECTIVE

Candida parapsilosis species complex, an important set of non-albicans Candida species, is known to cause candidaemia particularly in neonates and infants. However, the incidence has increased in recent years, owing to higher numbers of at individuals at risk for these infections. Our objective was to evaluate the in vitro susceptibility of clinical isolates of C. parapsilosis complex isolates from Iran to seven antifungal drugs.

MATERIAL AND METHODS

One hundred-one clinical isolates of C. parapsilosis species complex cultured from humans were included. Species identification had been previously confirmed by combined phenotypic characteristics, matrix-assisted laser desorption ionization-time of flight mass spectrometry-based assay and reconfirmed by DNA sequence analysis of the ITS rDNA region and D1/D2 gene. Minimum inhibitory concentrations (MICs) for amphotericin B, fluconazole, itraconazole, voriconazole, posaconazole, micafungin and anidulafungin were determined against well-characterized isolates by broth microdilution susceptibility testing according to the CLSI M27-A3 guideline.

RESULTS

Species identifications were performed on 101 isolates, of which 88 (87.2%) C. parapsilosis sensu stricto and 13 (12.8%) C. orthopsilosis. Amphotericin B and posaconazole were the most active drugs with 100% of isolates being wild-type (WT). Voriconazole and micafungin, 99% of isolates were WT. The low activity was recorded for fluconazole and itraconazole with 93.1% and 89.1% of isolates being WT, respectively. At the species level, all Candida parapsilosis sensu stricto isolates were WT to amphotericin B and posaconazole and all Candida orthopsilosis isolates were WT to amphotericin B, voriconazole, posaconazole, anidulafungin and micafungin. In contrast, the highest rate of non-WT was observed in C. orthopsilosis to itraconazole (4 of 13, 30.8%).

CONCLUSIONS

Although almost all of the tested drugs demonstrated potent activity against C. parapsilosis species complex, it seems that more especially C. orthopsilosis isolates had decreased susceptibility to itraconazole. Further studies are needed to determine how these findings may switch into in vivo efficacy.

Aflatoxin M1 contamination level in Iranian milk and dairy products: a systematic review and meta-analysis

Aflatoxin M1 is a derivate of aflatoxin B1 and an important contaminant of milk and dairy products. This systematic review and meta-analysis was conducted on relevant Persian and English original articles in national and international databases with no time limits until 1 January 2018. In total 605 articles were found among which 70 articles met the inclusion criteria for meta-analysis. The prevalence (95% confidence interval (CI)) and mean concentration (95% CI) of aflatoxin M1 was found to be 64% (53-75%) and 39.7 ng/l (31.9-47.4 ng/l) in raw milk, 95% (89-98%) and 62.3 ng/l (40.6-84 ng/l) in pasteurised milk, 71% (56-84%) and 60.1 ng/l (30.9-89.3 ng/l) in sterilised milk, 59% (20-93%) and 5.5 ng/l (3.3-7.7 ng/l) in breast milk and 72% (61-81%) and 82.3 ng/kg (63.7-100.9 ng/kg) in dairy products. In general, 9% (4-16%) of milks and 10% (4-17%) of dairy products had aflatoxin M1 in concentrations exceeding the permitted level of Iranian standards (500 ng/l). Based on the maximum permitted aflatoxin M1 concentration in standards of Europe (50 ng/l), these percentages increase to 25% (18-32%) for milks and 18% (9-29%) for dairy products. According to the results, further control and preventive measures should be applied on livestock feeds because decreased aflatoxin B1 contamination at this level results in decreased aflatoxin M1 in milk and dairy products.