REliability of consensus-based segMentatIoN in raDiomic feature reproducibility (REMIND): A word of caution.

OBJECTIVE: To evaluate the reliability of consensus-based segmentation in terms of reproducibility of radiomic features. METHODS: In this retrospective study, three tumor data sets were investigated: breast cancer (n = 30), renal cell carcinoma (n = 30), and pituitary macroadenoma (n = 30). MRI was utilized for breast and pituitary data sets, while CT was used for renal data set. 12 readers participated in the segmentation process. Consensus segmentation was created by making corrections on a previous region or volume of interest. Four experiments were designed to evaluate the reproducibility of radiomic features. Reliability was assessed with intraclass correlation coefficient (ICC) with two cut-off values: 0.75 and 0.9. RESULTS: Considering the lower bound of the 95% confidence interval and the ICC threshold of 0.90, at least 61% of the radiomic features were not reproducible in the inter-consensus analysis. In the susceptibility experiment, at least half (54%) became non-reproducible when the first reader is replaced with a different reader. In the intra-consensus analysis, at least about one-third (32%) were non-reproducible when the same second reader segmented the image over the same first reader two weeks later. Compared to inter-reader analysis based on independent single readers, the inter-consensus analysis did not statistically significantly improve the rates of reproducible features in all data sets and analyses. CONCLUSIONS: Despite the positive connotation of the word "consensus", it is essential to REMIND that consensus-based segmentation has significant reproducibility issues. Therefore, the usage of consensus-based segmentation alone should be avoided unless a reliability analysis is performed, even if it is not practical in clinical settings.

NEgatiVE results in Radiomics research (NEVER): A meta-research study of publication bias in leading radiology journals.

PURPOSE: The purpose of this study was to conduct a meta-research of radiomics-related articles for the publication of negative results, with a focus on the leading clinical radiology journals due to their purportedly high editorial standards. METHODS: A literature search was performed in PubMed to identify original research studies on radiomics (last search date: August 16th, 2022). The search was restricted to studies published in Q1 clinical radiology journals indexed by Scopus and Web of Science. Following an a priori power analysis based on our null hypothesis, a random sampling of the published literature was conducted. Besides the six baseline study characteristics, a total of three items about publication bias were evaluated. Agreement between raters was analyzed. Disagreements were resolved through consensus. Statistical synthesis of the qualitative evaluations was presented. RESULTS: Following a priori power analysis, we included a random sample of 149 publications in this study. Most of the publications were retrospective (95%; 142/149), based on private data (91%; 136/149), centered on a single institution (75%; 111/149), and lacked external validation (81%; 121/149). Slightly fewer than half (44%; 66/149) made no comparison to non-radiomic approaches. Overall, only one study (1%; 1/149) reported negative results for radiomics, yielding a statistically significant binomial test (p < 0.0001). CONCLUSION: The top clinical radiology journals almost never publish negative results, having a strong bias toward publishing positive results. Almost half of the publications did not even compare their approach with a non-radiomic method.

Transparency in Artificial Intelligence Research: a Systematic Review of Availability Items Related to Open Science in Radiology and Nuclear Medicine.

RATIONALE AND OBJECTIVES: Reproducibility of artificial intelligence (AI) research has become a growing concern. One of the fundamental reasons is the lack of transparency in data, code, and model. In this work, we aimed to systematically review the radiology and nuclear medicine papers on AI in terms of transparency and open science. MATERIALS AND METHODS: A systematic literature search was performed in PubMed to identify original research studies on AI. The search was restricted to studies published in Q1 and Q2 journals that are also indexed on the Web of Science. A random sampling of the literature was performed. Besides six baseline study characteristics, a total of five availability items were evaluated. Two groups of independent readers including eight readers participated in the study. Inter-rater agreement was analyzed. Disagreements were resolved with consensus. RESULTS: Following eligibility criteria, we included a final set of 194 papers. The raw data was available in about one-fifth of the papers (34/194; 18%). However, the authors made their private data available only in one paper (1/161; 1%). About one-tenth of the papers made their pre-modeling (25/194; 13%), modeling (28/194; 14%), or post-modeling files (15/194; 8%) available. Most of the papers (189/194; 97%) did not attempt to create a ready-to-use system for real-world usage. Data origin, use of deep learning, and external validation had statistically significantly different distributions. The use of private data alone was negatively associated with the availability of at least one item (p<0.001). CONCLUSION: Overall rates of availability for items were poor, leaving room for substantial improvement.

Evaluation and comparison of eighteen SARS-CoV-2 antibody assays from seven different companies to assess its diagnostic role in SARS-CoV-2 infections.

The diagnostic performance of reverse transcriptase polymerase chain reaction (RT-PCR) decreases during the late acute stage of the corona virus disease (COVID-19) infection; hence, serological assays can be used for disease diagnosis in patients non-protected through vaccinations at this stage. The objective of this study was to assess the diagnostic accuracy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests in current/past infections, determine proper testing time, and check the accuracy of cutoff values. In this study, 18 Ig (immunoglobulin) G, IgM, IgA, and total antibody serological assays were performed using 839 samples. Positive sera (n=132) were collected during the first 5 months after the patients were symptomatic and tested positive for the SARS-CoV-2 RT-PCR test; they were grouped as 0-10, 10-15, >15 days according to the symptom onset. Negative sera (N=707) were obtained from patients with lupus before the pandemic. The performance of IgG and total antibody assays was better than those of IgA, IgM, and IgA-IgM for all post-symptom groups except for 0-10 days, which showed lower Ig assay sensitivity. During 10-15 and >15 days, >70% sensitivity to IgA, IgM, IgM-IgA assays and lower sensitivity were noted, respectively. The sensitivities of IgG and total antibody assays for group C were slightly lower than that of group B. There were no significant differences, but there were higher correlations between the methods or antigenic structures. Receiving operating characteristics (ROC) analysis revealed better cutoff values. For the diagnosis of late acute/past SARS-CoV-2 infection, serological tests can be performed on unvaccinated patients showing symptoms for ≥10 days. SARS-CoV-2 IgG and total antibodies were better diagnostic markers than IgM, IgA, and IgM+IgA, which were restricted to group B.

Unraveling Molecular Fingerprints of Catalytic Sulfur Poisoning at the Nanometer Scale with Near-Field Infrared Spectroscopy.

Fundamental understanding of catalytic deactivation phenomena such as sulfur poisoning occurring on metal/metal-oxide interfaces is essential for the development of high-performance heterogeneous catalysts with extended lifetimes. Unambiguous identification of catalytic poisoning species requires experimental methods simultaneously delivering accurate information regarding adsorption sites and adsorption geometries of adsorbates with nanometer-scale spatial resolution, as well as their detailed chemical structure and surface functional groups. However, to date, it has not been possible to study catalytic sulfur poisoning of metal/metal-oxide interfaces at the nanometer scale without sacrificing chemical definition. Here, we demonstrate that near-field nano-infrared spectroscopy can effectively identify the chemical nature, adsorption sites, and adsorption geometries of sulfur-based catalytic poisons on a Pd(nanodisk)/Al2O3 (thin-film) planar model catalyst surface at the nanometer scale. The current results reveal striking variations in the nature of sulfate species from one nanoparticle to another, vast alterations of sulfur poisoning on a single Pd nanoparticle as well as at the assortment of sulfate species at the active metal-metal-oxide support interfacial sites. These findings provide critical molecular-level insights crucial for the development of long-lifetime precious metal catalysts resistant toward deactivation by sulfur.

Immunohistochemical Analysis of E-Cadherin, p53 and Inhibin-α Expression in Hydatidiform Mole and Hydropic Abortion.

The purpose of this study was to investigate the role of E-cadherin, p53, and inhibin-α immunostaining in the differential diagnosis of hydropic abortion (HA), partial hydatidiform mole (PHM), and complete hydatidiform mole (CHM). E-cadherin, p53, and inhibin-α protein expression patterns were investigated immunohistochemically using paraffin -embedded tissue sections from histologically diagnosed cases of HA (n = 23), PHM (n = 24), and CHM (n = 23). Expression patterns of these markers were scored semi-quantitatively according to the staining intensity, percentage of positive cells, and immunoreactivity score. Classification of cases was established on histologic criteria and supported by the molecular genotyping. Immunostaining allowed the identification of specific cell types with E-cadherin, p53, and inhibin-α expression in all cases. E-cadherin expression was detected on the cell surface of villous cytotrophoblasts. We observed a marked decline in the expression of E-cadherin from HAs to PHMs to CHMs. The p53-positive reaction was restricted to the nucleus of villous cytotrophoblasts. Significantly increased p53 expression was observed in CHMs, compared with HAs and PHMs. The expression of inhibin-α was localised in the cytoplasm of villous syncytiotrophoblasts, and the expression of this marker was significantly higher in PHMs and CHMs than HAs. In conclusion, immunohistochemical analysis of E-cadherin, p53, and inhibin-α expression could serve as a useful adjunct to conventional methods in the differential diagnosis of HA, PHM, and CHM.