Lung ultrasound and supine chest X-ray use in modern adult intensive care: mapping 30 years of advancement (1993-2023).

In critically ill patients with acute respiratory failure, thoracic images are essential for evaluating the nature, extent and progression of the disease, and for clinical management decisions. For this purpose, computed tomography (CT) is the gold standard. However, transporting patients to the radiology suite and exposure to ionized radiation limit its use. Furthermore, a CT scan is a static diagnostic exam for the thorax, not allowing, for example, appreciation of "lung sliding". Its use is also unsuitable when it is necessary to adapt or decide to modify mechanical ventilation parameters at the bedside in real-time. Therefore, chest X-ray and lung ultrasound are today's contenders for shared second place on the podium to acquire a thoracic image, with their specific strengths and limitations. Finally, electrical impedance tomography (EIT) could soon have a role, however, its assessment is outside the scope of this review. Thus, we aim to carry out the following points: (1) analyze the advancement in knowledge of lung ultrasound use and the related main protocols adopted in intensive care units (ICUs) over the latest 30 years, reporting the principal publications along the way, (2) discuss how and when lung ultrasound should be used in a modern ICU and (3) illustrate the possible future development of LUS.

A Novel Automatic Algorithm to Support Lung Ultrasound Non-Expert Physicians in Interstitial Pneumonia Evaluation: A Single-Center Study.

INTRODUCTION: Lung ultrasound (LUS) is widely used in clinical practice for identifying interstitial lung diseases (ILDs) and assessing their progression. Although high-resolution computed tomography (HRCT) remains the gold standard for evaluating the severity of ILDs, LUS can be performed as a screening method or as a follow-up tool post-HRCT. Minimum training is needed to better identify typical lesions, and the integration of innovative artificial intelligence (AI) automatic algorithms may enhance diagnostic efficiency. AIM: This study aims to assess the effectiveness of a novel AI algorithm in automatic ILD recognition and scoring in comparison to an expert LUS sonographer. The "SensUS Lung" device, equipped with an automatic algorithm, was employed for the automatic recognition of the typical ILD patterns and to calculate an index grading of the interstitial involvement. METHODS: We selected 33 Caucasian patients in follow-up for ILDs exhibiting typical HRCT patterns (honeycombing, ground glass, fibrosis). An expert physician evaluated all patients with LUS on twelve segments (six per side). Next, blinded to the previous evaluation, an untrained operator, a non-expert in LUS, performed the exam with the SensUS device equipped with the automatic algorithm ("SensUS Lung") using the same protocol. Pulmonary functional tests (PFT) and DLCO were conducted for all patients, categorizing them as having reduced or preserved DLCO. The SensUS device indicated different grades of interstitial involvement named Lung Staging that were scored from 0 (absent) to 4 (peak), which was compared to the Lung Ultrasound Score (LUS score) by dividing it by the number of segments evaluated. Statistical analyses were done with Wilcoxon tests for paired values or Mann-Whitney for unpaired samples, and correlations were performed using Spearman analysis; p < 0.05 was considered significant. RESULTS: Lung Staging was non-inferior to LUS score in identifying the risk of ILDs (median SensUS 1 [0-2] vs. LUS 0.67 [0.25-1.54]; p = 0.84). Furthermore, the grade of interstitial pulmonary involvement detected with the SensUS device is directly related to the LUS score (r = 0.607, p = 0.002). Lung Staging values were inversely correlated with forced expiratory volume at first second (FEV1%, r = -0.40, p = 0.027), forced vital capacity (FVC%, r = -0.39, p = 0.03) and forced expiratory flow (FEF) at 25th percentile (FEF25%, r = -0.39, p = 0.02) while results directly correlated with FEF25-75% (r = 0.45, p = 0.04) and FEF75% (r = 0.43, p = 0.01). Finally, in patients with reduced DLCO, the Lung Staging was significantly higher, overlapping the LUS (reduced median 1 [1-2] vs. preserved 0 [0-1], p = 0.001), and overlapping the LUS (reduced median 18 [4-20] vs. preserved 5.5 [2-9], p = 0.035). CONCLUSIONS: Our data suggest that the considered AI automatic algorithm may assist non-expert physicians in LUS, resulting in non-inferior-to-expert LUS despite a tendency to overestimate ILD lesions. Therefore, the AI algorithm has the potential to support physicians, particularly non-expert LUS sonographers, in daily clinical practice to monitor patients with ILDs. The adopted device is user-friendly, offering a fully automatic real-time analysis. However, it needs proper training in basic skills.

Fragility Score: a REMS-based indicator for the prediction of incident fragility fractures at 5 years.

BACKGROUND: Accurate estimation of the imminent fragility fracture risk currently represents a challenging task. The novel Fragility Score (FS) parameter, obtained during a Radiofrequency Echographic Multi Spectrometry (REMS) scan of lumbar or femoral regions, has been developed for the non-ionizing estimation of skeletal fragility. AIMS: The aim of this study was to assess the performance of FS in the early identification of patients at risk for incident fragility fractures with respect to bone mineral density (BMD) measurements. METHODS: Data from 1989 Caucasians of both genders were analysed and the incidence of fractures was assessed during a follow-up period up to 5 years. The diagnostic performance of FS to discriminate between patients with and without incident fragility fracture in comparison to that of the BMD T-scores measured by both Dual X-ray Absorptiometry (DXA) and REMS was assessed through ROC analysis. RESULTS: Concerning the prediction of generic osteoporotic fractures, FS provided AUC = 0.811 for women and AUC = 0.780 for men, which resulted in AUC = 0.715 and AUC = 0.758, respectively, when adjusted for age and body mass index (BMI). For the prediction of hip fractures, the corresponding values were AUC = 0.780 for women and AUC = 0.809 for men, which became AUC = 0.735 and AUC = 0.758, respectively, after age- and BMI-adjustment. Overall, FS showed the highest prediction ability for any considered fracture type in both genders, resulting always being significantly higher than either T-scores, whose AUC values were in the range 0.472-0.709. CONCLUSION: FS displayed a superior performance in fracture prediction, representing a valuable diagnostic tool to accurately detect a short-term fracture risk.

A new standard scoring for interstitial pneumonia based on quantitative analysis of ultrasonographic data: A study on COVID-19 patients.

OBJECTIVE: To assess the effectiveness of 3 novel lung ultrasound (LUS)-based parameters: Pneumonia Score and Lung Staging for pneumonia staging and COVID Index, indicating the probability of SARS-CoV-2 infection. METHODS: Adult patients admitted to the emergency department with symptoms potentially related to pneumonia, healthy volunteers and clinical cases from online accessible databases were evaluated. The patients underwent a clinical-epidemiological questionnaire and a LUS acquisition, following a 14-zone protocol. For each zone, a Pneumonia score from 0 to 4 was assigned by the algorithm and by an expert operator (kept blind with respect to the algorithm results) on the basis of the identified imaging signs and the patient Lung Staging was derived as the highest observed score. The output of the operator was considered as the ground truth. The algorithm calculated also the COVID Index by combining the automatically identified LUS markers with the questionnaire answers and compared with the nasopharyngeal swab results. RESULTS: Overall, 556 patients were analysed. A high agreement between the algorithm assignments and the expert operator evaluations was observed, both for Pneumonia Score and Lung Staging, with the latter having sensitivity and specificity over 92% both in the discrimination between healthy/sick patients and between sick patients with mild/severe pneumonia. Regarding the COVID Index, an area under the curve of 0.826 was observed for the classification of patients with/without SARS-CoV-2. CONCLUSION: The proposed methodology allowed the identification and staging of patients suffering from pneumonia with high accuracy. Moreover, it provided the probability of being infected by SARS-CoV-2.

First assessment of bone mineral density in healthy pregnant women by means of Radiofrequency Echographic Multi Spectrometry (REMS) technology.

OBJECTIVE: The maternal bone structure is the largest calcium reserve for the fetus during pregnancy, and this is claimed to lead to a bone mineral density (BMD) reduction in pregnant women. The primary outcome of the present work was to assess the BMD in a group of healthy pregnant women. STUDY DESIGN: In this prospective case - control observational study, a non-consecutive group of pregnant women with uncomplicated pregnancy at or >37 weeks were enrolled at the unit of Obstetrics and Gynecology, University of Parma, from February to December 2020. The study subjects were submitted to a sonographic examination of the proximal femur with Radiofrequency Echographic Multi Spectrometry (REMS) technology to quantify the BMD of the femur. The BMD values obtained in the study group were compared with those of a control group of non-pregnant women matched for age, ethnicity and pre-pregnant body mass index (BMI). RESULTS: Overall, 78 pregnant women at 39.1 ±â€¯1.5 weeks were assessed. Compared with non-pregnant women, the femoral BMD values measured in pregnancy using REMS were significant lower (0.769 ±â€¯0.094 g/cm2 vs 0.831 ±â€¯0.101 g/cm2, p = 0.0001) with a mean BMD reduction of 8.1%. The femoral neck BMD presented a positive correlation with the pre-pregnant BMI (p = 0.0004) and a negative correlation with the maternal age (p < 0.0001). In addition, a lower femoral neck BMD in Caucasian ethnicity compared with non-Caucasian was noted (p < 0.0001). CONCLUSION: In this exploratory and proof of concept study, for the first time, a decreased BMD has been objectively demonstrated in pregnant compared with non-pregnant women by means of REMS technology. New studies are required to assess the longitudinal changes of maternal bone density throughout the pregnancy.

In-situ photo-assisted deposition of silver particles on hydrogel fibers for antibacterial applications.

Silver nanoparticles (AgNPs) have attracted intensive research interest and have been recently incorporated in polymers, medical devices, hydrogels and burn dressings to control the proliferation of microorganisms. In this study a novel silver antibacterial coating was deposited for the first time on hydrogel fibers through an in-situ photo-chemical reaction. Hydrogel blends obtained by mixing different percentages of silver-treated and untreated fibers were characterized by thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). Four different fluids, such as phosphate buffered saline (PBS), simulated body fluid (SBF), chemical simulated wound fluid (cSWF), and deionized water (DI water), were used for evaluating the swelling properties. The results obtained confirmed that the presence of silver did not affect the properties of the hydrogel. Moreover, the results obtained through inductively coupled plasma mass spectrometry (ICP-MS) demonstrated very low silver release values, thus indicating the perfect adhesion of the silver coating to the substrate. Good antibacterial capabilities were demonstrated by any hydrogel blend on Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) through agar diffusion tests and optical density readings.