Training radiology residents to evaluate deep myometrial invasion in endometrial cancer patients on MRI: A learning curve study.

PURPOSE: To evaluate the impact of a four-month training program on radiology residents' diagnostic accuracy in assessing deep myometrial invasion (DMI) in endometrial cancer (EC) using MRI. METHOD: Three radiology residents with limited EC MRI experience participated in the training program, which included conventional didactic sessions, case-centric workshops, and interactive classes. Utilizing a training dataset of 120 EC MRI scans, trainees independently assessed subsets of cases over five reading sessions. Each subset consisted of 30 scans, the first and the last with the same cases, for a total of 150 reads. Diagnostic accuracy metrics, assessment time (rounded to the nearest minute), and confidence levels (using a 5-point Likert scale) were recorded. The learning curve was obtained plotting the diagnostic accuracy of the three trainees and the average over the subsets. Anatomopathological results served as the reference standard for DMI presence. RESULTS: The three trainees exhibited heterogeneous starting point, with a learning curve and a trend to more homogeneous performance with training. The diagnostic accuracy of the average trainee raised from 64 % (56 %-76 %) to 88 % (80 %-94 %) across the five subsets (p < 0.001). Reductions in assessment time (5.92 to 4.63 min, p < 0.018) and enhanced confidence levels (3.58 to 3.97, p = 0.12) were observed. Improvements in sensitivity, specificity, positive predictive value, and negative predictive value were noted, particularly for specificity which raised from 56 % (41 %-68 %) in the first to 86 % (74 %-94 %) in the fifth subset (p = 0.16). Although not reaching statistical significance, these advancements aligned the trainees with literature performance benchmarks. CONCLUSIONS: The structured training program significantly enhanced radiology residents' diagnostic accuracy in assessing DMI for EC on MRI, emphasizing the effectiveness of active case-based training in refining oncologic imaging skills within radiology residency curricula.

The zebrafish (Danio rerio) embryo-larval contact assay combined with biochemical biomarkers and swimming performance in sewage sludge and hydrochar hazard assessment.

Hydrothermal carbonization is considered a powerful technology to convert sewage sludge (SS) into a valuable carbonaceous solid known as hydrochar (HC). Up to now criteria for landfill application of SS and HC are based only on physicochemical properties and levels of pollutant residues. Nevertheless, to ensure their safe environmental applications it is mandatory to develop biosensors which can provide relevant information on their toxic potential for natural ecosystems. Therefore, this study aimed to assess the suitability of a contact assay using zebrafish embryo/larvae combined with sub-lethal end-points to evaluate the hazard associated with SS and related HC exposure. A suite of biomarkers was also applied on larvae, related to detoxification and oxidative stress as the activity of Ethoxyresorufin-O-deethylase, glutathione-S-transferase, and catalase, the content of reactive oxygen species and the behavioral assay using the DanioVision™ chamber. Legacy priority pollutants were also measured either in SS and HC tested samples and in contact waters. The exposure to SS caused higher lethality compared to HC. No significant changes in the activity of oxidative stress markers was observed upon exposure to both matrices. The behavioral test showed a hypoactivity condition in larvae exposed to both SS and HC with the effects of SS stronger than HC. Chemical analysis revealed the presence of trace elements and halogenated compounds in either SS, HC. Heavy metals were also released in contact waters, while volatile hydrocarbons (C6-C10) and halogenated compounds resulted below LOD (<0.05 µ L-1). Our study highlights the suitability of zebrafish embryotoxicity test, coupled with behavioral traits, as screening tool for assessing potential risks, associated with the landfill application of both SS and HC, for aquatic wildlife.

Aryl hydrocarbon reporter gene bioassay for screening polyhalogenated dibenzo-p-dioxins/furans and dioxin-like polychlorinated biphenyls in hydrochar and sewage sludge.

The suitability of the AhR reporter gene bioassays to screen the presence of polychlorinated dibenzo-p-dioxins/furans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (dl-PCBs) in sewage sludge (SL) and related hydrochar (HC) was here investigated. Samples of SL obtained from six WWTPs were processed by hydrothermal carbonization to obtain the resultant HCs and both tested with DR-CALUX® bioassay. Levels of PCDD/Fs and dl-PCBs were also determined analytically in the same samples by GC-MS/MS. Bioanalytical Toxicity Equivalent values (BEQ) resulted in one order of magnitude higher in HC compared to SL samples and those obtained from the dl-PCBs fraction higher than those from PCDD/Fs. BEQ and TEQWHO values, the latter obtained by GC-MS/MS analysis on the same matrices, were highly correlated showing also a similar trend in the six WWTPs (RS= 0.8252, p < 0.001; Pearson's R RP =0.8029, p < 0.01). The suitability of AhR bioassays and in particular of the DR-CALUX® to screen the presence and biological activity of legacy organohalogen compounds in both SL and HC matrices was demonstrated for the first time which support their usage for the assessment of potential risks associated with their further environmental applications.

Data on coastal dunes vulnerability of eleven microtidal wave-dominated beaches of Sardinia (Italy, western Mediterranean).

This article contains data about the values of the Dune Vulnerability Index (DVI) and the Partial Index Vulnerability (IVp) of eleven coastal dune systems located in Sardinia (Italy, western Mediterranean). Specifically, we present the values of 59 variables that summarize the condition of the studied dune systems, clustered in five groups: Geomorphological Condition (GCD), Marine Influence (MI), Aeolian Influence (AI), Vegetation Condition (VC), and Human Effects (HE). Data were collected during numerous field surveys and using aerial-photos. This dataset can be useful to evaluate the coastal dune vulnerability of several Sardinian beaches in order to drive local coastal managers towards an efficient management.