Artificial intelligence applied to image-guided radiation therapy (IGRT): a systematic review by the Young Group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO).

INTRODUCTION: The advent of image-guided radiation therapy (IGRT) has recently changed the workflow of radiation treatments by ensuring highly collimated treatments. Artificial intelligence (AI) and radiomics are tools that have shown promising results for diagnosis, treatment optimization and outcome prediction. This review aims to assess the impact of AI and radiomics on modern IGRT modalities in RT. METHODS: A PubMed/MEDLINE and Embase systematic review was conducted to investigate the impact of radiomics and AI to modern IGRT modalities. The search strategy was "Radiomics" AND "Cone Beam Computed Tomography"; "Radiomics" AND "Magnetic Resonance guided Radiotherapy"; "Radiomics" AND "on board Magnetic Resonance Radiotherapy"; "Artificial Intelligence" AND "Cone Beam Computed Tomography"; "Artificial Intelligence" AND "Magnetic Resonance guided Radiotherapy"; "Artificial Intelligence" AND "on board Magnetic Resonance Radiotherapy" and only original articles up to 01.11.2022 were considered. RESULTS: A total of 402 studies were obtained using the previously mentioned search strategy on PubMed and Embase. The analysis was performed on a total of 84 papers obtained following the complete selection process. Radiomics application to IGRT was analyzed in 23 papers, while a total 61 papers were focused on the impact of AI on IGRT techniques. DISCUSSION: AI and radiomics seem to significantly impact IGRT in all the phases of RT workflow, even if the evidence in the literature is based on retrospective data. Further studies are needed to confirm these tools' potential and provide a stronger correlation with clinical outcomes and gold-standard treatment strategies.

Artificial intelligence and radiation effects on brain tissue in glioblastoma patient: preliminary data using a quantitative tool.

PURPOSE: The quantification of radiotherapy (RT)-induced functional and morphological brain alterations is fundamental to guide therapeutic decisions in patients with brain tumors. The magnetic resonance imaging (MRI) allows to define structural RT-brain changes, but it is unable to evaluate early injuries and to objectively quantify the volume tissue loss. Artificial intelligence (AI) tools extract accurate measurements that permit an objective brain different region quantification. In this study, we assessed the consistency between an AI software (Quibim Precision® 2.9) and qualitative neruroradiologist evaluation, and its ability to quantify the brain tissue changes during RT treatment in patients with glioblastoma multiforme (GBM). METHODS: GBM patients treated with RT and subjected to MRI assessment were enrolled. Each patient, pre- and post-RT, undergoes to a qualitative evaluation with global cerebral atrophy (GCA) and medial temporal lobe atrophy (MTA) and a quantitative assessment with Quibim Brain screening and hippocampal atrophy and asymmetry modules on 19 extracted brain structures features. RESULTS: A statistically significant strong negative association between the percentage value of the left temporal lobe and the GCA score and the left temporal lobe and the MTA score was found, while a moderate negative association between the percentage value of the right hippocampus and the GCA score and the right hippocampus and the MTA score was assessed. A statistically significant strong positive association between the CSF percentage value and the GCA score and a moderate positive association between the CSF percentage value and the MTA score was found. Finally, quantitative feature values showed that the percentage value of the cerebro-spinal fluid (CSF) statistically differences between pre- and post-RT. CONCLUSIONS: AI tools can support a correct evaluation of RT-induced brain injuries, allowing an objective and earlier assessment of the brain tissue modifications.

Cervical spine injury: clinical and medico-legal overview.

Spinal trauma is an important cause of disability worldwide. Injury to the cervical spine (CS) occurs frequently after major trauma. 5-10% of patients with blunt trauma have a cervical spine injury. The cervical spine accounts for ~ 50% of all spinal injuries. Determination of CS stability is a common challenge in the acute care setting of patients with trauma. Several issues, indeed, are of particular concern: who needs CS imaging; what imaging should be obtained; when should computed tomography (CT), magnetic resonance imaging (MRI), or flexion/extension (F/E) radiographs be obtained; and how is significant ligamentous injury excluded in the comatose patient. CT and MRI both have roles to play. This article aims to present the different imaging to frame techniques to be used with greater precision in the acute event also for the purpose of planning the next therapeutic process. An overview of the applicability of the same methods in forensic pathology is also provided highlighting possible future biomarker to ease in diagnosis of acute TBI.

Radiomics textural features by MR imaging to assess clinical outcomes following liver resection in colorectal liver metastases.

PURPOSE: To assess the efficacy of radiomics features obtained by T2-weighted sequences to predict clinical outcomes following liver resection in colorectal liver metastases patients. METHODS: This retrospective analysis was approved by the local Ethical Committee board and radiological databases were interrogated, from January 2018 to May 2021, to select patients with liver metastases with pathological proof and MRI study in pre-surgical setting. The cohort of patients included a training set and an external validation set. The internal training set included 51 patients with 61 years of median age and 121 liver metastases. The validation cohort consisted a total of 30 patients with single lesion with 60 years of median age. For each volume of interest, 851 radiomics features were extracted as median values using PyRadiomics. Nonparametric test, intraclass correlation, receiver operating characteristic (ROC) analysis, linear regression modelling and pattern recognition methods (support vector machine (SVM), k-nearest neighbours (KNN), artificial neural network (NNET) and decision tree (DT)) were considered. RESULTS: The best predictor to discriminate expansive versus infiltrative front of tumour growth was obtained by wavelet_LHL_gldm_DependenceNonUniformityNormalized with an accuracy of 82%; to discriminate high grade versus low grade or absent was the wavelet_LLH_glcm_Imc1 with accuracy of 88%; to differentiate the mucinous type of tumour was the wavelet_LLH_glcm_JointEntropy with accuracy of 92% while to identify tumour recurrence was the wavelet_LLL_glcm_Correlation with accuracy of 85%. Linear regression model increased the performance obtained with respect to the univariate analysis exclusively in the discrimination of expansive versus infiltrative front of tumour growth reaching an accuracy of 90%, a sensitivity of 95% and a specificity of 80%. Considering significant texture metrics tested with pattern recognition approaches, the best performance was reached by the KNN in the discrimination of the tumour budding considering the four textural predictors obtaining an accuracy of 93%, a sensitivity of 81% and a specificity of 97%. CONCLUSIONS: Ours results confirmed the capacity of radiomics to identify as biomarkers, several prognostic features that could affect the treatment choice in patients with liver metastases, in order to obtain a more personalized approach.

Structured reporting of computed tomography in the staging of colon cancer: a Delphi consensus proposal.

BACKGROUND: Structured reporting (SR) in radiology is becoming increasingly necessary and has been recognized recently by major scientific societies. This study aims to build structured CT-based reports in colon cancer during the staging phase in order to improve communication between the radiologist, members of multidisciplinary teams and patients. MATERIALS AND METHODS: A panel of expert radiologists, members of the Italian Society of Medical and Interventional Radiology, was established. A modified Delphi process was used to develop the SR and to assess a level of agreement for all report sections. Cronbach's alpha (Cα) correlation coefficient was used to assess internal consistency for each section and to measure quality analysis according to the average inter-item correlation. RESULTS: The final SR version was built by including n = 18 items in the "Patient Clinical Data" section, n = 7 items in the "Clinical Evaluation" section, n = 9 items in the "Imaging Protocol" section and n = 29 items in the "Report" section. Overall, 63 items were included in the final version of the SR. Both in the first and second round, all sections received a higher than good rating: a mean value of 4.6 and range 3.6-4.9 in the first round; a mean value of 5.0 and range 4.9-5 in the second round. In the first round, Cronbach's alpha (Cα) correlation coefficient was a questionable 0.61. In the first round, the overall mean score of the experts and the sum of scores for the structured report were 4.6 (range 1-5) and 1111 (mean value 74.07, STD 4.85), respectively. In the second round, Cronbach's alpha (Cα) correlation coefficient was an acceptable 0.70. In the second round, the overall mean score of the experts and the sum of score for structured report were 4.9 (range 4-5) and 1108 (mean value 79.14, STD 1.83), respectively. The overall mean score obtained by the experts in the second round was higher than the overall mean score of the first round, with a lower standard deviation value to underline greater agreement among the experts for the structured report reached in this round. CONCLUSIONS: A wide implementation of SR is of critical importance in order to offer referring physicians and patients optimum quality of service and to provide researchers with the best quality data in the context of big data exploitation of available clinical data. Implementation is a complex procedure, requiring mature technology to successfully address the multiple challenges of user-friendliness, organization and interoperability.

The Dental-BIOfilm Detection TECHnique (D-BioTECH): A Proof of Concept of a Patient-Based Oral Hygiene.

To date, no strong long-term data have been reported about new innovative clinical protocols to manage oral hygiene. An improper management of oral hygiene may lead to an increase in dental implant failure, and to an increase in infective complications in prosthetic rehabilitation. Personalized techniques are strongly required in dentistry and dental hygiene. A customized and personalized approach to oral hygiene is crucial in ensuring not only effective treatment, but also a careful analysis of the general health status of the patient involved in the therapeutic process. D-BioTECH is an acronym for Dental BIOfilm Detection Technique: it is based on a tailored approach to patients, ensuring that the operator actively interacts with the patient and their specific needs, especially during the domiciliary therapy. D-BioTECH is an approach to preventive care: in D-BioTECH, both dental hygienists and dentists play a central role. The use of a personalized approach to oral hygiene is the first step towards increasing implant and prosthesis survival rate; moreover, personalized medicine is strategic for managing and preventing the biological complications associated with several dental risk factors.

Quantitative imaging decision support (QIDSTM) tool consistency evaluation and radiomic analysis by means of 594 metrics in lung carcinoma on chest CT scan.

OBJECTIVE: To evaluate the consistency of the quantitative imaging decision support (QIDSTM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan. MATERIALS AND METHODS: We included, retrospectively, 150 patients with histologically confirmed lung cancer who underwent chemotherapy and baseline and follow-ups CT scans. Using the QIDSTM platform, 3 radiologists segmented each lesion and automatically collected the longest diameter and the density mean value. Inter-observer variability, Bland Altman analysis and Spearman's correlation coefficient were performed. QIDSTM tool consistency was assessed in terms of agreement rate in the treatment response classification. Kruskal Wallis test and the least absolute shrinkage and selection operator (LASSO) method with 10-fold cross validation were used to identify radiomic metrics correlated with lesion size change. RESULTS: Good and significant correlation was obtained between the measurements of largest diameter and of density among the QIDSTM tool and the radiologists measurements. Inter-observer variability values were over 0.85. HealthMyne QIDSTM tool quantitative volumetric delineation was consistent and matched with each radiologist measurement considering the RECIST classification (80-84%) while a lower concordance among QIDSTM and the radiologists CHOI classification was observed (58-63%). Among 594 extracted metrics, significant and robust predictors of RECIST response were energy, histogram entropy and uniformity, Kurtosis, coronal long axis, longest planar diameter, surface, Neighborhood Grey-Level Different Matrix (NGLDM) dependence nonuniformity and low dependence emphasis as Volume, entropy of Log(2.5 mm), wavelet energy, deviation and root man squared. CONCLUSION: In conclusion, we demonstrated that HealthMyne quantitative volumetric delineation was consistent and that several radiomic metrics extracted by QIDSTM were significant and robust predictors of RECIST response.

Intrahepatic cholangiocarcinoma and its differential diagnosis at MRI: how radiologist should assess MR features.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is the second most common type of primary hepatic malignancy. Aim of this work is to analyse the features of ICC and its differential diagnosis at MRI, assessing two categories intraparenchymal and peribiliary lesions. METHODS: The study population included 88 patients with histological diagnosis of ICCs: 61 with mass-forming type, 23 with periductal-infiltrating tumours and 4 with intraductal-growing type. As a control study groups, we identified: 86 consecutive patients with liver colorectal intrahepatic metastases (mCRC) (groups A); 35 consecutive patients with peribiliary metastases (groups B); 62 consecutive patients (groups C) with hepatocellular carcinoma (HCC); 18 consecutive patients (groups D) with combined hepatocellular cholangiocarcinoma (cHCC-CCA); and 26 consecutive patients (groups E) with hepatic hemangioma. For all lesions, magnetic resonance (MR) features were assessed according to Liver Imaging Reporting and Data System (LI-RADS) version 2018. The liver-specific gadolinium ethoxybenzyl dimeglumine-EOB (Primovist, Bayer Schering Pharma, Germany), was employed. Chi-square test was employed to analyse differences in percentage values of categorical variable, while the nonparametric Kruskal-Wallis test was used to test for statistically significant differences between the median values of the continuous variables. However, false discovery rate adjustment according to Benjamin and Hochberg for multiple testing was considered. RESULTS: T1- and T2-weighted signal intensity (SI), restricted diffusion, transitional phase (TP) and hepatobiliary phase (HP) aspects allowed the differentiation between study group (mass-forming ICCs) and each other control group (A, C, D, E) with statistical significance, while arterial phase (AP) appearance allowed the differentiation between study group and the control groups C and D with statistical significance and PP appearance allowed the differentiation between study group and the control groups A, C and D with statistical significance. Instead, no MR feature allowed the differentiation between study group (periductal-infiltrating type) and control group B. CONCLUSION: T1 and T2 W SI, restricted diffusion, TP and HP appearance allowed the differentiation between mass-forming ICCs and mimickers with statistical significance, while AP appearance allowed the differentiation between study group and the control groups C and D with statistical significance and PP appearance allowed the differentiation between study group and the control groups A, C and D.

Delta radiomics: a systematic review.

BACKGROUND: Radiomics can provide quantitative features from medical imaging that can be correlated with various biological features and clinical endpoints. Delta radiomics, on the other hand, consists in the analysis of feature variation at different acquisition time points, usually before and after therapy. The aim of this study was to provide a systematic review of the different delta radiomics approaches. METHODS: Eligible articles were searched in Embase, PubMed, and ScienceDirect using a search string that included free text and/or Medical Subject Headings (MeSH) with three key search terms: "radiomics", "texture", and "delta". Studies were analysed using QUADAS-2 and the RQS tool. RESULTS: Forty-eight studies were finally included. The studies were divided into preclinical/methodological (five studies, 10.4%); rectal cancer (six studies, 12.5%); lung cancer (twelve studies, 25%); sarcoma (five studies, 10.4%); prostate cancer (three studies, 6.3%), head and neck cancer (six studies, 12.5%); gastrointestinal malignancies excluding rectum (seven studies, 14.6%), and other disease sites (four studies, 8.3%). The median RQS of all studies was 25% (mean 21% ± 12%), with 13 studies (30.2%) achieving a quality score < 10% and 22 studies (51.2%) < 25%. CONCLUSIONS: Delta radiomics shows potential benefit for several clinical endpoints in oncology (differential diagnosis, prognosis and prediction of treatment response, and evaluation of side effects). Nevertheless, the studies included in this systematic review suffer from the bias of overall low quality, so that the conclusions are currently heterogeneous, not robust, and not replicable. Further research with prospective and multicentre studies is needed for the clinical validation of delta radiomics approaches.

Artificial intelligence to codify lung CT in Covid-19 patients.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (CT). Asymptomatic patients may also have lung lesions on imaging. CT investigation in patients with suspicion Covid-19 pneumonia involves the use of the high-resolution technique (HRCT). Artificial intelligence (AI) software has been employed to facilitate CT diagnosis. AI software must be useful categorizing the disease into different severities, integrating the structured report, prepared according to subjective considerations, with quantitative, objective assessments of the extent of the lesions. In this communication, we present an example of a good tool for the radiologist (Thoracic VCAR software, GE Healthcare, Italy) in Covid-19 diagnosis (Pan et al. in Radiology, 2020. https://doi.org/10.1148/radiol.2020200370). Thoracic VCAR offers quantitative measurements of the lung involvement. Thoracic VCAR can generate a clear, fast and concise report that communicates vital medical information to referring physicians. In the post-processing phase, software, thanks to the help of a colorimetric map, recognizes the ground glass and differentiates it from consolidation and quantifies them as a percentage with respect to the healthy parenchyma. AI software therefore allows to accurately calculate the volume of each of these areas. Therefore, keeping in mind that CT has high diagnostic sensitivity in identifying lesions, but not specific for Covid-19 and similar to other infectious viral diseases, it is mandatory to have an AI software that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one.

Dimensional changes of buccal bone plate in immediate implants inserted through open flap, open flap and bone grafting and flapless techniques: A cone-beam computed tomography randomized controlled clinical trial.

OBJECTIVES: To assess through cone-beam computed tomography (CBCT) buccal alveolar bone alterations after immediate implant placement using the following techniques: open flap and grafting (flap-graft), open flap and no grafting (flap-nograft) and flapless and no grafting (noflap-nograft). MATERIALS AND METHODS: This was a three-armed parallel group randomized clinical trial with allocation ratio 1:1:1. Patients were eligible in case they needed immediate implant replacing teeth in maxillary premolar area, with sufficient buccal bone support. CBCT was performed immediately after the intervention and 6 months later. The main outcomes were CBCT measurements performed at apical (A-EA), medial (M-EM) and external and internal implant bevel level (B-EB, B-IB) and vertical defect depth (DP). Pain and discomfort, time of surgery and complications were recorded. Differences between groups were estimated through ANOVA tests and post-hoc Scheffe's analysis for pairwise comparisons. Multiple regressions were conducted to estimate influence of gingival biotype and baseline marginal gap dimension. RESULTS: Forty-five patients were recruited and randomized to treatments with one lost to follow-up. Analysis of variance showed that the effect of treatment technique was not relevant for all horizontal and vertical outcomes. The three techniques exhibited almost complete fill of marginal gap, with a mean residual vertical gap of 0.27 mm and horizontal gap of 0.5 mm. Regression models indicated a positive effect of thick biotype on gap filling and dimensional bone reduction. The noflap-nograft technique resulted less painful. CONCLUSIONS: The option of noflap-nograft surgery in post-extraction implants allows for minimal surgical intervention with comparable buccal bone changes and gap filling after a follow-up of 6 months in sites with sufficient buccal bone support.

High-dose intensity-modulated radiation therapy as primary treatment of prostate cancer: genitourinary/gastrointestinal toxicity and outcomes, a single-institution experience.

PURPOSE: Prostatectomy, radiotherapy and watchful waiting are the main therapeutic options available for local stage of prostate cancer (PCa). We report our experience on 394 patients affected by prostate cancer primarily treated with high-dose, image-guided, IMRT, focusing on gastrointestinal, genitourinary toxicities and biochemical control. METHODS: From July 2003 to August 2014, 394 patients were treated with radical high-dose radiotherapy (HDRT) for prostate cancer; the mean total radiation dose was 79 Gy in standard fractions. Hormonal therapy (HT) was administered to 7.6% of low-risk patients, to 20.3% of intermediate-risk patients and to 72% of high-risk patients. Patients were evaluated for biochemical failure, local recurrence (LR) and metastases. RESULTS: Ninety-seven patients (26.65%) developed acute GU toxicity at the medium dose of 25.4 Gy, grade 1 (G1) or grade 2 (G2) in 94 cases. Only 16 patients (4.06%) reported chronic GU toxicity (G1 or G2), and one case developed G3 cystitis. No G3 GI acute and late toxicity were detected. Fifty-six (14.2%) patients experienced LR, 26 (6.6%) developed metastases and 70 patients (17.8%) were deceased. Gleason sum score > 7 was predictive for worse overall survival (GS = 7 was borderline) and for metastasis. No factors resulted predictive for local relapse. HT pre-RT had been demonstrated as a negative predictor for OS and DFS-DM. CONCLUSIONS: Data confirm the safety of HDRT for PCa. Treatment was efficient with low toxicity profile. Moreover, continued technologic advancements, as image-guided radiotherapy, could lead to further reduction in toxicity, thus increasing the therapeutic index.

Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT.

PURPOSE: Image texture analysis (TA) is a heterogeneity quantifying approach that cannot be appreciated by the naked eye, and early evidence suggests that TA has great potential in the field of oncology. The aim of this study is to evaluate parotid gland texture analysis (TA) combined with formal dosimetry as a factor for predicting severe late xerostomia in patients undergoing radiation therapy for head and neck cancers. METHODS: We performed a retrospective analysis of patients treated at our Radiation Oncology Unit between January 2010 and December 2015, and selected the patients whose normal dose constraints for the parotid gland (mean dose < 26 Gy for the bilateral gland) could not be satisfied due to the presence of positive nodes close to the parotid glands. The parotid gland that showed the higher V30 was contoured on CT simulation and analysed with LifeX Software©. TA parameters included features of grey-level co-occurrence matrix (GLCM), neighbourhood grey-level dependence matrix (NGLDM), grey-level run length matrix (GLRLM), grey-level zone length matrix (GLZLM), sphericity, and indices from the grey-level histogram. We performed a univariate and multivariate analysis between all the texture parameters, the volume of the gland, the normal dose parameters (V30 and Mean Dose), and the development of severe chronic xerostomia. RESULTS: Seventy-eight patients were included and 25 (31%) developed chronic xerostomia. The TA parameters correlated with severe chronic xerostomia included V30 (OR 5.63), Dmean (OR 5.71), Kurtosis (OR 0.78), GLCM Correlation (OR 1.34), and RLNU (OR 2.12). The multivariate logistic regression showed a significant correlation between V30 (0.001), GLCM correlation (p: 0.026), RLNU (p: 0.011), and chronic xerostomia (p < 0.001, R2:0.664). CONCLUSIONS: Xerostomia represents an important cause of morbidity for head and neck cancer survivors after radiation therapy, and in certain cases normal dose constraints cannot be satisfied. Our results seem promising as texture analysis could enhance the normal dose constraints for the prediction of xerostomia.

Associations between Radiomics and Genomics in Non-Small Cell Lung Cancer Utilizing Computed Tomography and Next-Generation Sequencing: An Exploratory Study.

BACKGROUND: Radiomics, an evolving paradigm in medical imaging, involves the quantitative analysis of tumor features and demonstrates promise in predicting treatment responses and outcomes. This study aims to investigate the predictive capacity of radiomics for genetic alterations in non-small cell lung cancer (NSCLC). METHODS: This exploratory, observational study integrated radiomic perspectives using computed tomography (CT) and genomic perspectives through next-generation sequencing (NGS) applied to liquid biopsies. Associations between radiomic features and genetic mutations were established using the Area Under the Receiver Operating Characteristic curve (AUC-ROC). Machine learning techniques, including Support Vector Machine (SVM) classification, aim to predict genetic mutations based on radiomic features. The prognostic impact of selected gene variants was assessed using Kaplan-Meier curves and Log-rank tests. RESULTS: Sixty-six patients underwent screening, with fifty-seven being comprehensively characterized radiomically and genomically. Predominantly males (68.4%), adenocarcinoma was the prevalent histological type (73.7%). Disease staging is distributed across I/II (38.6%), III (31.6%), and IV (29.8%). Significant correlations were identified with mutations of ROS1 p.Thr145Pro (shape_Sphericity), ROS1 p.Arg167Gln (glszm_ZoneEntropy, firstorder_TotalEnergy), ROS1 p.Asp2213Asn (glszm_GrayLevelVariance, firstorder_RootMeanSquared), and ALK p.Asp1529Glu (glcm_Imc1). Patients with the ROS1 p.Thr145Pro variant demonstrated markedly shorter median survival compared to the wild-type group (9.7 months vs. not reached, p = 0.0143; HR: 5.35; 95% CI: 1.39-20.48). CONCLUSIONS: The exploration of the intersection between radiomics and cancer genetics in NSCLC is not only feasible but also holds the potential to improve genetic predictions and enhance prognostic accuracy.

[From anatomy to image: the cranial nerves at MRI]. / Dall'anatomia all'immagine: la visualizzazione dei nervi cranici in RM.

In this article, we review the expected course of each of the 12 cranial nerves. Traditional magnetic resonance imaging depicts only the larger cranial nerves but SSFP sequences of magnetic resonance imaging are capable of depicting the cisternal segments of 12 cranial nerves and also provide submillimetric spatial resolution.

[µCT analysis of mandibular molars before and after instrumentation by Reciproc files]. / Analisi anatomiche di molari mandibolari pre- e post-strumentazione con Reciproc mediante µTC.

Cleaning and shaping are important section for the root canal treatment. A number of different methodologies have been developed to overcome these problems, including the introduction of rotary instruments nickel-titanium (NiTi). In endodontics NiTi have been shown to significantly reduce procedural errors compared to manual techniques of instrumentation. The efficiency of files is related to many factor. Although previous investigations that have used µCT analysis were hampered by insufficient resolution or projection incorrect. The new generation of µCT performance best offer, as micron resolution and accurate measurement software for evaluating the accurate anatomy of the root canal. The aim the paper was to evaluate the efficiency of Reciproc files in root canal treatment, evaluated before and after instrumentation by using µ-CT analysis.

[Cytological diagnosis of lymph nodes by instrumental guide: ultrasonography and CT]. / La diagnosi citologica dei linfonodi con guida strumentale: ecografia e TC.

Imaging techniques, such as ultrasound imaging, computed tomography, positron emission tomography or magnetic resonance imaging, are highly accurate procedures for the detection of lymph node enlargement, but none of them has the same sensitivity in the biological definition and in the cause of enlargement. Therefore, a direct evaluation of corresponding lymph nodes is necessary in most cases and fine needle cytology (FNC) is one of the most frequently used techniques for this purpose. The same imaging procedures are often used to perform targeted biopsies including FNC. This study discusses procedures, indications, advantages and limitations of imaging techniques as a support to FNC.

Efficacy of ozonated water as a PS in photodynamic therapy: A tool for dental caries management? An in vitro study.

Background: The most prevalent noncommunicable disease in the world is dental caries; and when it is not adequately treated, it is usually associated with tooth loss or severe dental lesions. In fact, expensive care or tooth extraction may be necessary due to the negative effects dental caries have on general health. This is due to its frequent pain and secondary bacterial infections. The aim of this study was to investigate the activity of ozonated water as such and in combination with appropriate light radiation so as to perform a photodynamic treatment (PDT) against the cariogenic bacterium Streptococcus mutans. Design and methods: This work has been performed in vitro by using an S. mutans strain mainly structured in a biofilm status, reproducing the natural condition of the tooth infection. The ozone was tested at three different concentrations by using a commercial device able to generate different O3 formulations in water. The PDT treatment requires an appropriate light wavelength, evaluated in this work through the UV-Vis adsorption spectrum of the ozonated water. Results: The obtained results suggested an effective and synergic property of O3 and light at 460-470 nm against this microorganism. The most antibiofilm activity was observed using a concentration of ozone of 0.06 mg/L alone as well as with PDT treatment. Conclusions: The results are encouraging for additional research and in vitro/in vivo fresh experimental investigations to perform an exhaustive antimicrobial treatment protocol against the S. mutans tooth infection.

Epidemiological evaluation of patient compliance regarding oral health and hygiene during the COVID-19 period.

This work aimed to report values on oral hygiene habits at home during the pandemic and compare the differences between previous oral hygiene habits. A total of 1,136 questionnaires were filled in via a link sent through email to the patients. The answers show that although they had more time during the pandemic, they spent less time on dental and tongue hygiene. Dental and tongue hygiene are key to maintaining systemic health. The questionnaire was sent by e-mail to 1,136 male and female patients throughout Italy. Demonstrate and understand whether patients during the pandemic cleaned and spent time cleaning and maintaining their teeth and tongue hygiene. The questionnaire testifies to the fact that it is not the time but the patient's compliance and motivation that makes the difference. OBJECTIVE: This work aimed to report values regarding oral hygiene habits at home during the pandemic and compare the difference with previous oral hygiene habits. METHODS: This study was performed anonymously and had patients answer an online questionnaire. The questionnaire consisted of 11 closed-answer questions (except 1) concerning oral hygiene habits at home at the time of COVID-19 and participant characteristics, including gender and age. A total of 1,136 questionnaires were filled in via a link sent by email to the patients. RESULTS: Among the 1,136 patients examined, 32.4% (372) were male and 67.6% (775) were female, and almost half (47.9%) of the patients who answered the questionnaire were aged 18-40 years. Patients who participated in our survey were asked questions related to dental and tongue hygiene. The answers showed that although they had more time during the pandemic, they brushed their teeth less and did not brush their tongues regularly. CONCLUSION: Patients with periodontal problems usually have less time for brushing and do not have good plaque control. The questionnaire showed the opposite, such that the patient's compliance and motivation matters more than time. Thus, dentists and dental hygienists must encourage and make patients understand the importance of oral hygiene at home.