Repeatability and reproducibility of quantitative cervical strain elastography (E-Cervix) in pregnancy

Strain elastography of the uterine cervix may be useful in the diagnosis and prediction of obstetric complications. The inability to obtain quantitative results, with only the possibility of visual semiquantitative evaluation of the obtained elastograms, has been the limitation of the method thus far. E-Cervix is a software program that uses intrinsic compression to excite tissue and allows the evaluation of quantitative parameters on the basis of pixel distribution in an elastogram. The aim of this study was to assess the repeatability and reproducibility of quantitative cervical strain elastography (E-Cervix) of the uterine cervix and to assess the correlation of the obtained parameters with selected clinical features of patients in the third trimester of pregnancy. In total, 222 patients participated in the study. We assessed 5 ultrasound parameters: elasticity index (ECI), hardness ratio (HR), internal os strain (IOS), external os strain (EOS) and IOS/EOS ratio. Each study was performed according to a predetermined standardized protocol. For all assessed elastographic parameters, we obtained good intra- and interobserver reproducibility. The interclass correlation coefficient (ICC) ranged from 0.77 to 0.838 for intraobserver variability and from 0.771 to 0.826 for interobserver variability. We demonstrated a significant correlation of some obtained elastographic parameters with the basic clinical features of patients, such as age, the number of previous caesarean sections, pregnancy weight and BMI. In each case, the correlation was very low. Quantitative elastographic assessment with the use of E-Cervix is characterized by good repeatability. Some clinical features may affect the value of the parameters obtained. The clinical relevance of this interference requires further investigation.

High-Frequency Three-Dimensional Lumen Volume Ultrasound Is a Sensitive Method to Detect Early Aneurysmal Change in Elastase-Induced Murine Abdominal Aortic Aneurysm

Objective The aim of this study was to investigate the reproducibility of anterior–posterior diameter (APdmax) and three-dimensional lumen volume (3DLV) measurements of abdominal aortic aneurysms (AAA) in a classical murine AAA model. We also compared the magnitude of change in the aortic size detected with each method of assessment. Methods Periadventitial application of porcine pancreatic elastase (PPE AAA) or sham surgery was performed in two cohorts of mice. Cohort 1 was used to assess for observer variability with the APdmax and 3DLV measurements. Cohort 2 highlighted the relationship between APdmax and 3DLV and changes in AAA detected. Results There was no significant observer variability detected with APdmax measurement. Similarly, no significant intraobserver variability was evident with 3DLV; however, a small but significant interobserver difference was present. APdmax and 3DLV measurements of PPE AAA significantly correlated. However, changes in the AAA morphology were detected earlier with 3DLV. Conclusion APdmax and 3DLV are both reliable methods for measuring an AAA. Both these methods correlate with each other. However, changes in AAA morphology were detected earlier with 3DLV, which is important to detect subtle but important changes to aortic geometry in a laboratory setting. 3DLV measurement of AAA is a simple, reproducible, and comprehensive method for assessing changes in disease morphology.

Intra- and Interobserver Variability in Magnetic Resonance Imaging Measurements in Rectal Cancer Patients

Colorectal cancer is the second most common cancer in Europe, and accurate lymph node staging in rectal cancer patients is essential for the selection of their treatment. MRI lymph node staging is complex, and few studies have been published regarding its reproducibility. This study assesses the inter- and intraobserver variability in lymph node size, apparent diffusion coefficient (ADC) measurements, and morphological characterization among inexperienced and experienced radiologists. Four radiologists with different levels of experience in MRI rectal cancer staging analyzed 36 MRI scans of 36 patients with rectal adenocarcinoma. Inter- and intraobserver variation was calculated using interclass correlation coefficients and Cohens-kappa statistics, respectively. Inter- and intraobserver agreement for the length and width measurements was good to excellent, and for that of ADC it was fair to good. Interobserver agreement for the assessment of irregular border was moderate, heterogeneous signal was fair, round shape was fair to moderate, and extramesorectal lymph node location was moderate to almost perfect. Intraobserver agreement for the assessment of irregular border was fair to substantial, heterogeneous signal was fair to moderate, round shape was fair to moderate, and extramesorectal lymph node location was substantial to almost perfect. Our data indicate that subjective variables such as morphological characteristics are less reproducible than numerical variables, regardless of the level of experience of the observers.

Agreement and Intraobserver Variability in Detection of Helicobacter pylori Infection Using Routine Histology, H. pylori Immunohistochemical Stain, and Warthin-Starry Special Stain on Gastric Tissue Biopsy Samples

Introduction/Objective Helicobacter pylori (HP) is a prevalent cause of gastritis in the US and worldwide. Accurate detection of the organism is important for appropriate treatment. Diagnosis is made using immunohistochemistry and special stains including Warthin-Starry stain (WS) which is low cost, technically easy to perform on tissue sections, and can be automated. We aimed to assess interobserver variability, reproducibility and validity of hematoxylin and eosin stain (H&E), WS and anti-Helicobacter pylori immunohistochemical staining (HP-IHC) for the histopathological identification and evaluation of HP organisms on gastric mucosa biopsies. Methods/Case Report We prospectively evaluated gastric biopsies from ten adult patients. These patients underwent upper gastrointestinal endoscopy with subsequent biopsy for various abdominal complaints. Seven of the ten biopsies (7/10) were HP infection positive, and three cases (3/10) were HP negative by H&E stain and HP-IHC (determined by GI Pathologist). The presence or absence and density of HP, were assessed on H&E, HP-IHC and WS in blinded fashion by five general surgical (GS) pathologists. The GS pathologists assessed the cases for presence and density of HP using the semi-quantitative modified Sydney classification (none, mild, moderate, and severe). Percentage agreement and interobserver variablilty using Cohen-Kappas statistics (KS) were calculated. Results (if a Case Study enter NA) The percentage agreement for presence or absence of HP in the biopsies with H&E, HP-IHC and WS stains were 91%, 98% and 99%, respectively. The interobserver agreement for evaluation of presence of HP was excellent with WS staining method (Overall KS = 0.737 95%, Confidence Interval (CI) = 0.501- 0.973) and HP-IHC (Overall KS = 0.783, 95% CI = 0.585-0.980). Agreement for H&E was moderate (Overall KS = 0.532, 95% CI= 0.392-0.672). HP density agreement was excellent using WS and HP-IHC and H&E was in the moderate range. Conclusion This study found excellent interobserver agreement using IHC and WS. While IHC is the most specific stain, WS is more sensitive in identifying the shape and morphology of HP organisms and is an efficient and low-cost alternative with excellent morphology in general surgical practice.

Uncertainty Quantification of Regional Cardiac Tissue Properties in Arrhythmogenic Cardiomyopathy Using Adaptive Multiple Importance Sampling

Introduction: Computational models of the cardiovascular system are widely used to simulate cardiac (dys)function. Personalization of such models for patient-specific simulation of cardiac function remains challenging. Measurement uncertainty affects accuracy of parameter estimations. In this study, we present a methodology for patient-specific estimation and uncertainty quantification of parameters in the closed-loop CircAdapt model of the human heart and circulation using echocardiographic deformation imaging. Based on patient-specific estimated parameters we aim to reveal the mechanical substrate underlying deformation abnormalities in patients with arrhythmogenic cardiomyopathy (AC).Methods: We used adaptive multiple importance sampling to estimate the posterior distribution of regional myocardial tissue properties. This methodology is implemented in the CircAdapt cardiovascular modeling platform and applied to estimate active and passive tissue properties underlying regional deformation patterns, left ventricular volumes, and right ventricular diameter. First, we tested the accuracy of this method and its inter- and intraobserver variability using nine datasets obtained in AC patients. Second, we tested the trueness of the estimation using nine in silico generated virtual patient datasets representative for various stages of AC. Finally, we applied this method to two longitudinal series of echocardiograms of two pathogenic mutation carriers without established myocardial disease at baseline.Results: Tissue characteristics of virtual patients were accurately estimated with a highest density interval containing the true parameter value of 9% (95% CI [0–79]). Variances of estimated posterior distributions in patient data and virtual data were comparable, supporting the reliability of the patient estimations. Estimations were highly reproducible with an overlap in posterior distributions of 89.9% (95% CI [60.1–95.9]). Clinically measured deformation, ejection fraction, and end-diastolic volume were accurately simulated. In presence of worsening of deformation over time, estimated tissue properties also revealed functional deterioration.Conclusion: This method facilitates patient-specific simulation-based estimation of regional ventricular tissue properties from non-invasive imaging data, taking into account both measurement and model uncertainties. Two proof-of-principle case studies suggested that this cardiac digital twin technology enables quantitative monitoring of AC disease progression in early stages of disease.

Accuracy of New Deep Learning Model-Based Segmentation and Key-Point Multi-Detection Method for Ultrasonographic Developmental Dysplasia of the Hip (DDH) Screening

Hip joint ultrasonographic (US) imaging is the golden standard for developmental dysplasia of the hip (DDH) screening. However, the effectiveness of this technique is subject to interoperator and intraobserver variability. Thus, a multi-detection deep learning artificial intelligence (AI)-based computer-aided diagnosis (CAD) system was developed and evaluated. The deep learning model used a two-stage training process to segment the four key anatomical structures and extract their respective key points. In addition, the check angle of the ilium body balancing level was set to evaluate the system’s cognitive ability. Hence, only images with visible key anatomical points and a check angle within ±5° were used in the analysis. Of the original 921 images, 320 (34.7%) were deemed appropriate for screening by both the system and human observer. Moderate agreement (80.9%) was seen in the check angles of the appropriate group (Cohen’s κ = 0.525). Similarly, there was excellent agreement in the intraclass correlation coefficient (ICC) value between the measurers of the alpha angle (ICC = 0.764) and a good agreement in beta angle (ICC = 0.743). The developed system performed similarly to experienced medical experts; thus, it could further aid the effectiveness and speed of DDH diagnosis.

Manual versus semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging: evaluation of similarity and comparison of segmentation times

Objective: To evaluate the degree of similarity between manual and semiautomatic segmentation of soft-tissue sarcomas on magnetic resonance imaging (MRI). Materials and Methods: This was a retrospective study of 15 MRI examinations of patients with histopathologically confirmed soft-tissue sarcomas acquired before therapeutic intervention. Manual and semiautomatic segmentations were performed by three radiologists, working independently, using the software 3D Slicer. The Dice similarity coefficient (DSC) and the Hausdorff distance were calculated in order to evaluate the similarity between manual and semiautomatic segmentation. To compare the two modalities in terms of the tumor volumes obtained, we also calculated descriptive statistics and intraclass correlation coefficients (ICCs). Results: In the comparison between manual and semiautomatic segmentation, the DSC values ranged from 0.871 to 0.973. The comparison of the volumes segmented by the two modalities resulted in ICCs between 0.9927 and 0.9990. The DSC values ranged from 0.849 to 0.979 for intraobserver variability and from 0.741 to 0.972 for interobserver variability. There was no significant difference between the semiautomatic and manual modalities in terms of the segmentation times (p > 0.05). Conclusion: There appears to be a high degree of similarity between manual and semiautomatic segmentation, with no significant difference between the two modalities in terms of the time required for segmentation.

Point-of-care lung ultrasound in COVID-19 patients: inter- and intra-observer agreement in a prospective observational study

With an urgent need for bedside imaging of coronavirus disease 2019 (COVID-19), this study’s main goal was to assess inter- and intraobserver agreement in lung ultrasound (LUS) of COVID-19 patients. In this single-center study we prospectively acquired and evaluated 100 recorded ten-second cine-loops in confirmed COVID-19 intensive care unit (ICU) patients. All loops were rated by ten observers with different subspeciality backgrounds for four times by each observer (400 loops overall) in a random sequence using a web-based rating tool. We analyzed inter- and intraobserver variability for specific pathologies and a semiquantitative LUS score. Interobserver agreement for both, identification of specific pathologies and assignment of LUS scores was fair to moderate (e.g., LUS score 1 Fleiss’ κ = 0.27; subpleural consolidations Fleiss’ κ = 0.59). Intraobserver agreement was mostly moderate to substantial with generally higher agreement for more distinct findings (e.g., lowest LUS score 0 vs. highest LUS score 3 (median Fleiss’ κ = 0.71 vs. 0.79) or air bronchograms (median Fleiss’ κ = 0.72)). Intraobserver consistency was relatively low for intermediate LUS scores (e.g. LUS Score 1 median Fleiss’ κ = 0.52). We therefore conclude that more distinct LUS findings (e.g., air bronchograms, subpleural consolidations) may be more suitable for disease monitoring, especially with more than one investigator and that training material used for LUS in point-of-care ultrasound (POCUS) should pay refined attention to areas such as B-line quantification and differentiation of intermediate LUS scores.

Feasibility, Reproducibility and Validation of Right Ventricular Volume and Function Assessment Using Three-Dimensional Echocardiography

Three-dimensional echocardiography (3DE) is advised for right ventricular (RV) assessment. Data regarding the optimal acquisition settings and optimization are still scarce. We aimed to evaluate the feasibility, reproducibility and validation of 3DE for RV volume and function assessment, using cardiac magnetic resonance (CMR) as gold standard. Thirty healthy volunteers and 36 consecutive patients were prospectively included. CMR was performed in the latter. Standard apical four-chamber view (A4CV), focused A4CV and modified A4CV were used for 3DE RV acquisition. Feasibility (and the effect of changes in settings) was evaluated. Intra and interobserver analyses were performed by three observers (expert vs. novice). RV parameters by echocardiography were compared to CMR. Feasibility of acquisition was 16.7% for A4CV, 80.0% for focused A4CV and 16.7% for modified A4CV. Changes in settings had no significant influence on feasibility and further analysis. Intraobserver variability was good in both expert and novice, interobserver variability was good between experienced observers. Compared to CMR, 3DE volumes were significantly lower with fair to moderate correlation (EDV: 91.1 ± 24.4 mL vs. 144.3 ± 43.0 mL (p < 0.001), r = 0.653 and ESV: 48.1 ± 16.4 mL vs. 60.4 ± 21.2 mL (p < 0.001), r = 0.530, by multi-beat 3DE and CMR respectively). These findings suggest that standardization is needed in order to implement this technique in clinical practice, thus further studies are required.

Ultrasound imaging of the fetal optic nerve from a different plane

Objective In this study, we aimed to visualize the fetal optic nerve and its sheath in a lateral oblique plane by ultrasound. Methods This cross-sectional prospective study was conducted at 20–22 weeks of gestation on healthy pregnant women who applied to our perinatology clinic for anomaly screening. Optic nerve sheath diameter (ONSD) measurements were taken from the lateral orbital and the retroorbital planes twice by the same sonographer. Ultrasound durations were recorded. Intraobserver variability was calculated for both techniques. The Bland-Altman analysis was performed for the lateral orbital technique. Results A total of 45 pregnant women were evaluated in the study. The intraclass correlation coefficient value of the lateral orbital technique was 0.722 (p<0.001), suggesting that the ONSD was measured similarly by the same observer. The ONSD mean measured by the lateral orbital (LO) technique was higher than the ONSD mean measured by the retroorbital (RO) technique (2.10±0.13 vs 1.21±0.13 mm, p<0.001). The ONSD measurement with the LO technique was determined to be more time-effective than the RO technique (129.6±31.3 vs 228.2±32.7 sec, p<0.001). Conclusion It is demonstrated that by using the lateral orbital technique, the optic nerve and its sheath can be visualized separately without the shadowing artifact of the lens. This technique also takes less time than the RO technique. There is a need for more extensive research on this subject with magnetic resonance imaging (MRI) confirmation.