A Systematic Review of Automated Segmentation Methods and Public Datasets for the Lung and its Lobes and Findings on Computed Tomography Images.

OBJECTIVES: Automated computational segmentation of the lung and its lobes and findings in X-Ray based computed tomography (CT) images is a challenging problem with important applications, including medical research, surgical planning, and diagnostic decision support. With the increase in large imaging cohorts and the need for fast and robust evaluation of normal and abnormal lungs and their lobes, several authors have proposed automated methods for lung assessment on CT images. In this paper we intend to provide a comprehensive summarization of these methods. METHODS: We used a systematic approach to perform an extensive review of automated lung segmentation methods. We chose Scopus, PubMed, and Scopus to conduct our review and included methods that perform segmentation of the lung parenchyma, lobes or internal disease related findings. The review was not limited by date, but rather by only including methods providing quantitative evaluation. RESULTS: We organized and classified all 234 included articles into various categories according to methodological similarities among them. We provide summarizations of quantitative evaluations, public datasets, evaluation metrics, and overall statistics indicating recent research directions of the field. CONCLUSIONS: We noted the rise of data-driven models in the last decade, especially due to the deep learning trend, increasing the demand for high-quality data annotation. This has instigated an increase of semi-supervised and uncertainty guided works that try to be less dependent on human annotation. In addition, the question of how to evaluate the robustness of data-driven methods remains open, given that evaluations derived from specific datasets are not general.

Rapidly deploying a COVID-19 decision support system in one of the largest Brazilian hospitals.

The COVID-19 pandemic generated research interest in automated models to perform classification and segmentation from medical imaging of COVID-19 patients, However, applications in real-world scenarios are still needed. We describe the development and deployment of COVID-19 decision support and segmentation system. A partnership with a Brazilian radiologist consortium, gave us access to 1000s of labeled computed tomography (CT) and X-ray images from São Paulo Hospitals. The system used EfficientNet and EfficientDet networks, state-of-the-art convolutional neural networks for natural images classification and segmentation, in a real-time scalable scenario in communication with a Picture Archiving and Communication System (PACS). Additionally, the system could reject non-related images, using header analysis and classifiers. We achieved CT and X-ray classification accuracies of 0.94 and 0.98, respectively, and Dice coefficient for lung and covid findings segmentations of 0.98 and 0.73, respectively. The median response time was 7 s for X-ray and 4 min for CT.

Automatic MR image quality evaluation using a Deep CNN: A reference-free method to rate motion artifacts in neuroimaging.

Motion artifacts on magnetic resonance (MR) images degrade image quality and thus negatively affect clinical and research scanning. Considering the difficulty in preventing patient motion during MR examinations, the identification of motion artifact has attracted significant attention from researchers. We propose an automatic method for the evaluation of motion corrupted images using a deep convolutional neural network (CNN). Deep CNNs has been used widely in image classification tasks. While such methods require a significant amount of annotated training data, a scarce resource in medical imaging, the transfer learning and fine-tuning approaches allow us to use a smaller amount of data. Here we selected four renowned architectures, initially trained on Imagenet contest dataset, to fine-tune. The models were fine-tuned using patches from an annotated dataset composed of 68 T1-weighted volumetric acquisitions from healthy volunteers. For training and validation 48 images were used, while the remaining 20 images were used for testing. Each architecture was fine-tuned for each MR axis, detecting the motion artifact per patches from the three orthogonal MR acquisition axes. The overall average accuracy for the twelve models (three axes for each of four architecture) was 86.3%. As our goal was to detect fine-grained corruption in the image, we performed an extensive search on lower layers from each of the four architectures, since they filter small regions in the original input. Experiments showed that architectures with fewer layers than the original ones reported the better results for image patches with an overall average accuracy of 90.4%. The accuracies per architecture were similar so we decided to explore all four architectures performing a result consensus. Also, to determine the probability of motion artifacts presence on the whole acquisition a combination of the three axes were performed. The final architecture consists of an artificial neural network (ANN) classifier combining all models from the four shallower architectures, which overall acquisition-based accuracy was 100.0%. The proposed method generalization was tested using three different MR data: (1) MR image acquired in epilepsy patients (93 acquisitions); (2) MR image presenting susceptibility artifact (22 acquisitions); and (3) MR image acquired from different scanner vendor (20 acquisitions). The achieved acquisition-based accuracy on generalization tests (1) 90.3%, (2) 63.6%, and (3) 75.0%) suggests that domain adaptation is necessary. Our proposed method can be rapidly applied to large amounts of image data, providing a motion probability p∈[0,1] per acquisition. This method output can be used as a scale to identify the motion corrupted images from the dataset, thus minimizing the time spent on visual quality control.

Hippocampus segmentation on epilepsy and Alzheimer's disease studies with multiple convolutional neural networks.

Background: Hippocampus segmentation on magnetic resonance imaging is of key importance for the diagnosis, treatment decision and investigation of neuropsychiatric disorders. Automatic segmentation is an active research field, with many recent models using deep learning. Most current state-of-the art hippocampus segmentation methods train their methods on healthy or Alzheimer's disease patients from public datasets. This raises the question whether these methods are capable of recognizing the hippocampus on a different domain, that of epilepsy patients with hippocampus resection. New Method: In this paper we present a state-of-the-art, open source, ready-to-use, deep learning based hippocampus segmentation method. It uses an extended 2D multi-orientation approach, with automatic pre-processing and orientation alignment. The methodology was developed and validated using HarP, a public Alzheimer's disease hippocampus segmentation dataset. Results and Comparisons: We test this methodology alongside other recent deep learning methods, in two domains: The HarP test set and an in-house epilepsy dataset, containing hippocampus resections, named HCUnicamp. We show that our method, while trained only in HarP, surpasses others from the literature in both the HarP test set and HCUnicamp in Dice. Additionally, Results from training and testing in HCUnicamp volumes are also reported separately, alongside comparisons between training and testing in epilepsy and Alzheimer's data and vice versa. Conclusion: Although current state-of-the-art methods, including our own, achieve upwards of 0.9 Dice in HarP, all tested methods, including our own, produced false positives in HCUnicamp resection regions, showing that there is still room for improvement for hippocampus segmentation methods when resection is involved.

Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks.

Manual annotation is considered to be the "gold standard" in medical imaging analysis. However, medical imaging datasets that include expert manual segmentation are scarce as this step is time-consuming, and therefore expensive. Moreover, single-rater manual annotation is most often used in data-driven approaches making the network biased to only that single expert. In this work, we propose a CNN for brain extraction in magnetic resonance (MR) imaging, that is fully trained with what we refer to as "silver standard" masks. Therefore, eliminating the cost associated with manual annotation. Silver standard masks are generated by forming the consensus from a set of eight, public, non-deep-learning-based brain extraction methods using the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. Our method consists of (1) developing a dataset with "silver standard" masks as input, and implementing (2) a tri-planar method using parallel 2D U-Net-based convolutional neural networks (CNNs) (referred to as CONSNet). This term refers to our integrated approach, i.e., training with silver standard masks and using a 2D U-Net-based architecture. We conducted our analysis using three public datasets: the Calgary-Campinas-359 (CC-359), the LONI Probabilistic Brain Atlas (LPBA40), and the Open Access Series of Imaging Studies (OASIS). Five performance metrics were used in our experiments: Dice coefficient, sensitivity, specificity, Hausdorff distance, and symmetric surface-to-surface mean distance. Our results showed that we outperformed (i.e., larger Dice coefficients) the current state-of-the-art skull-stripping methods without using gold standard annotation for the CNNs training stage. CONSNet is the first deep learning approach that is fully trained using silver standard data and is, thus, more generalizable. Using these masks, we eliminate the cost of manual annotation, decreased inter-/intra-rater variability, and avoided CNN segmentation overfitting towards one specific manual annotation guideline that can occur when gold standard masks are used. Moreover, once trained, our method takes few seconds to process a typical brain image volume using modern a high-end GPU. In contrast, many of the other competitive methods have processing times in the order of minutes.

An open, multi-vendor, multi-field-strength brain MR dataset and analysis of publicly available skull stripping methods agreement.

This paper presents an open, multi-vendor, multi-field strength magnetic resonance (MR) T1-weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The dataset is composed of images of older healthy adults (29-80 years) acquired on scanners from three vendors (Siemens, Philips and General Electric) at both 1.5 T and 3 T. CC-359 is comprised of 359 datasets, approximately 60 subjects per vendor and magnetic field strength. The dataset is approximately age and gender balanced, subject to the constraints of the available images. It provides consensus brain extraction masks for all volumes generated using supervised classification. Manual segmentation results for twelve randomly selected subjects performed by an expert are also provided. The CC-359 dataset allows investigation of 1) the influences of both vendor and magnetic field strength on quantitative analysis of brain MR; 2) parameter optimization for automatic segmentation methods; and potentially 3) machine learning classifiers with big data, specifically those based on deep learning methods, as these approaches require a large amount of data. To illustrate the utility of this dataset, we compared to the results of a supervised classifier, the results of eight publicly available skull stripping methods and one publicly available consensus algorithm. A linear mixed effects model analysis indicated that vendor (p-value<0.001) and magnetic field strength (p-value<0.001) have statistically significant impacts on skull stripping results.

Evaluation of periodontitis in hospital outpatients with major depressive disorder. A focus on gingival and circulating cytokines.

An imbalance in stimulated cytokine production is associated with the etiopathogenesis of numerous diseases such as major depressive disorder (MDD) and periodontal disease. Increased cytokine levels have been reported in the gingival crevicular fluid (GCF) of patients with MDD. Thirty-six outpatients with MDD participated in this study. Each outpatient was age-matched (± 3 years) with a healthy control (n=36). The patients were controlled for race and smoking habits. Unstimulated and stimulated interleukin 6 (IL-6), interleukin 1ß (IL-1ß), and interferon-γ (INF-γ) production in whole blood culture (WBC) and IL-6 and IL-1ß levels in the GCF were evaluated. Circulating levels of IL-6 and IL-1ß (unstimulated) as well as GCF IL-1ß were modestly lower in MDD patients, compared to the levels in age-matched controls (Mann-Whitney, p=0.002, 0.0075, ANCOVA, p=0.025, respectively). In the unstimulated group, there was no correlation between the levels of circulating IL-6 and GCF IL-6 (r=0.07, p=0.67), and between the levels of circulating IL-1ß and the IL-1ß level in the CGF (r=-0.08, p=0.63). In the LPS stimulation group, there was no correlation between the levels of circulating levels of IL-6 and GCF IL-6 (r=0. 02, p=0.91) or between the circulating IL-1ß and GCF IL-1ß (r=0.13, p=0.42). We observed modest immunosuppression in MDD patients (evaluated by no stimulation whole blood culture [WBC]), especially in patients with melancholic depression, chronic depression, and severe depression.

Divergence map from diffusion tensor imaging: concepts and application to corpus callosum.

This work proposes a novel approach to the analysis of Diffusion Tensor Imaging (DTI) by applying the mathematical concept of divergence, used in vector analysis. This is achieved by choosing an arbitrary direction of analysis and using this direction to transform the diffusion tensor field into an oriented vector field. The method was inspired by the idea of imposing a liquid flow inside the biological tissues, oriented in the direction of analysis, and watching the direction it would be expected to take as it flows through the paths created by the fibers. The experiments were conducted for the particular case of the analysis of the corpus callosum, using real DTI from several subjects. Results showed that the divergence map allows extraction of useful information about the spatial organization of the corpus callosum, providing a way to determine a reference plane that could be used, for example, in studies involving intersubject comparison.

Scaling and Root Planning decreases the Number of Melanosomes within Keratinocytes in Human Gingiva: Ultrastructural Analysis of Three Cases.

AIM: The aim of the present report was to evaluate the number of melanosomes within keratinocytes on pigmented gingiva, after and before scaling and root planning. MATERIALS AND METHODS: Inflamed gingiva biopsies were taken from three patients (group 1). Forty days after scaling and root planning, biopsies were collected from the homologous contralateral areas (group 2). Samples were fixed in 2% glutaraldehyde-2.5% formaldehyde (freshly prepared from paraformaldehyde) in 0.1 M sodium cacodylate buffer, pH 7.4 for 4 hours, and then processed for transmission electron microscopy. Eighty electron micrographs were evaluated for recording the number of granules by a cross-section grid. The granules that were on intersections were recorded as well as the points that appeared on the cytoplasm for calculating the volumetric density (Vd), i.e the volume that the melanosomes occupied into the cytoplasm of keratinocytes. The presence of melanosomes in different stages of maturation and distribution into the cells were recorded with the aid of a magnifying glass. For the statistical analysis, a student t-test was applied. RESULTS: Results of the present report showed that melanosomes within keratinocytes were present in a higher number in inflamed gingiva A (11.08 ± 1.47), B (3.16 ± 0.38) and C (4.92 ± 0.89) and decreased after resolving of gingival inflammation A (9.46 ± 0.88), B (1.73 ± 0.25) and C (0.76 ± 0.18). CONCLUSION: There is a possibility that inflammation influences the intensity of gingival melanin pigmentation. CLINICAL SIGNIFICANCE: The periodontal treatment appears to have an effect on gingival melanin pigmentation.

Etiology-based classification of brain white matter hyperintensity on magnetic resonance imaging.

Brain white matter lesions found upon magnetic resonance imaging are often observed in psychiatric or neurological patients. Individuals with these lesions present a more significant cognitive impairment when compared with individuals without them. We propose a computerized method to distinguish tissue containing white matter lesions of different etiologies (e.g., demyelinating or ischemic) using texture-based classifiers. Texture attributes were extracted from manually selected regions of interest and used to train and test supervised classifiers. Experiments were conducted to evaluate texture attribute discrimination and classifiers' performances. The most discriminating texture attributes were obtained from the gray-level histogram and from the co-occurrence matrix. The best classifier was the support vector machine, which achieved an accuracy of 87.9% in distinguishing lesions with different etiologies and an accuracy of 99.29% in distinguishing normal white matter from white matter lesions.

Automatic DTI-based parcellation of the corpus callosum through the watershed transform

INTRODUCTION: Parcellation of the corpus callosum (CC) in the midsagittal cross-section of the brain is of utmost importance for the study of diffusion properties within this structure. The complexity of this operation comes from the absence of macroscopic anatomical landmarks to help in dividing the CC into different callosal areas. In this paper we propose a completely automatic method for CC parcellation using diffusion tensor imaging (DTI). METHODS: A dataset of 15 diffusion MRI volumes from normal subjects was used. For each subject, the midsagital slice was automatically detected based on the Fractional Anisotropy (FA) map. Then, segmentation of the CC in the midsgital slice was performed using the hierarchical watershed transform over a weighted FA-map. Finally, parcellation of the CC was obtained through the application of the watershed transform from chosen markers. RESULTS: Parcellation results obtained were consistent for fourteen of the fifteen subjects tested. Results were similar to the ones obtained from tractography-based methods. Tractography confirmed that the cortical regions associated with each obtained CC region were consistent with the literature. CONCLUSIONS: A completely automatic DTI-based parcellation method for the CC was designed and presented. It is not based on tractography, which makes it fast and computationally inexpensive. While most of the existing methods for parcellation of the CC determine an average behavior for the subjects based on population studies, the proposed method reflects the diffusion properties specific for each subject. Parcellation boundaries are found based on the diffusion properties within each individual CC, which makes it more reliable and less affected by differences in size and shape among subjects.

Clinical and microbiologic evaluation, by real-time polymerase chain reaction, of non-surgical treatment of aggressive periodontitis associated with amoxicillin and metronidazole.

BACKGROUND: The aim of the present study is to evaluate the clinical and microbiologic changes resulting from non-surgical periodontal treatment associated with amoxicillin and metronidazole in individuals with aggressive periodontitis. METHODS: Fifteen individuals with aggressive periodontitis received non-surgical periodontal treatment and 45 days after completion of treatment were treated with antibiotics. Clinical data and samples of subgingival plaque were collected at baseline, 45 days after the non-surgical periodontal treatment, and 1 month after the use of antimicrobial agents. After 3 and 6 months, only clinical data were collected. The presence and quantification of Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis (Pg), Tannerella forsythia (Tf), Treponema denticola (Td), and Dialister pneumosintes were determined by real-time polymerase chain reaction. RESULTS: All clinical parameters, with the exception of clinical attachment level (CAL), had significantly (P <0.05) improved at the end of the third month after non-surgical therapy associated with antibiotics. There was significant (P <0.05) reduction in the quantities of Td and Tf. After 1 month, there were significant (P <0.05) reductions in the frequencies of Pg and Tf. CONCLUSION: Non-surgical mechanical treatment associated with the use of amoxicillin and metronidazole led to an improvement in all clinical parameters studied, except for CAL, and significantly reduced the amount of subgingival Tf and Td.

Subgingival ultrasonic instrumentation of residual pockets irrigated with essential oils: a randomized controlled trial.

AIM: To evaluate the clinical efficacy of subgingival ultrasonic instrumentation irrigated with essential oils (EOs) of residual periodontal pockets. MATERIAL AND METHODS: Sixty-four individuals with chronic periodontitis were invited to participate in this randomized, double-blind, parallel, and placebo-controlled clinical trial. All subjects received non-surgical periodontal therapy. After re-evaluation (baseline), residual pockets (pocket depth ≥5 mm) received test (ultrasonic instrumentation irrigated with EOs) or control therapy (ultrasonic instrumentation irrigated with negative control). Probing pocket depth (PPD), gingival recession (R), clinical attachment level (CAL), bleeding on probing (BOP), and plaque were assessed at baseline and after 4, 12, and 24 weeks. Differences between groups and changes over the course of time were analysed according to a generalized linear model. RESULTS: There was a significant reduction in PPD and BOP, as well as a significant CAL gain in the two groups (p<0.001). Nevertheless, there were no differences between the groups at any time of the study. When only initially deep pockets (PPD ≥7 mm) were analysed, a significantly greater CAL gain (p=0.03) and PPD reduction (p=0.01) was observed in the test group. CONCLUSION: The adjunctive use of EOs may promote significant CAL gain and PPD reduction in deep residual pockets.

Presence of periodontopathic bacteria in coronary arteries from patients with chronic periodontitis.

In this study the presence of periodontopathic pathogens in atheromatous plaques removed from coronary arteries of patients with chronic periodontitis and periodontally healthy subjects by PCR was detected. Our results indicate a significant association between the presence of Porphyromonas gingivalis and atheromas, and the periodontal bacteria in oral biofilm may find a way to reach arteries.

Clinical investigation of the efficacy of a commercial mouthrinse containing 0.05% cetylpyridinium chloride in preventing dental plaque.

OBJECTIVE: The objective of this independent, double-blind, seven-day clinical study was to assess the efficacy of a commercially available mouthrinse containing 0.05% cetylpyridinium chloride (CPC) in preventing dental plaque build-up relative to that of a control mouthrinse without 0.05% CPC. METHODS: Adult male and female subjects from the São Paulo, Brazil area reported to the clinical facility, having refrained from any oral hygiene procedures for 12 hours, and from eating, drinking, and smoking for four hours, for an assessment of the oral soft and hard tissues and a baseline dental plaque evaluation. Subjects qualifying for participation received a complete dental prophylaxis. Qualifying subjects were randomly assigned into one of the two treatment groups and were provided with their assigned mouthrinse, an adult soft-bristled toothbrush, and a commercially available fluoride toothpaste for home use. Over the seven-day period of home use, during which there were no restrictions regarding diet or smoking habits, subjects were instructed to brush their teeth for one minute twice daily (morning and evening) with the toothbrush and toothpaste supplied, to rinse their mouths with water after brushing, and then to rinse with 15 ml of their assigned mouthrinse for one minute before expectorating. The use of other oral hygiene products or procedures, such as floss or interdental stimulators, was not permitted during the study. After seven days of product use, subjects returned to the clinical facility having followed the same restrictions with respect to oral hygiene procedures, eating and drinking, as prior to the baseline examination, and the oral soft and hard tissue assessments and dental plaque evaluations were repeated. RESULTS: Forty-three subjects complied with the protocol and completed the study. Results demonstrated that after seven days of product use, mean plaque levels were statistically significantly lower (p < 0.05) than the pre-prophylaxis levels for both treatment groups. The mean plaque level for the CPC mouthrinse group was 46.1% of the pre-prophylaxis plaque level, whereas the mean plaque level for the control mouthrinse group was 75.5% of the pre-prophylaxis plaque level. The results demonstrate a statistically significant reduction in plaque build-up for the CPC mouthrinse group (29.3%) as compared to the control group. CONCLUSION: The overall results from this double-blind clinical study support the conclusion that, after seven days of product use, a mouthrinse containing 0.05% CPC provides significantly greater efficacy in preventing dental plaque build-up than a control mouthrinse without 0.05% CPC. As measurements were made 12 hours after final product use, the results also demonstrate that the CPC rinse provides 12-hour protection against dental plaque build-up.

Controle químico do biofilme dentário supragengival: revisão de literatura / Chemical control of supragingival dental biofilm

A remoção mecânica da placa bacteriana é a forma mais utilizada de higiene bucal. Entretanto, muitos indivíduos não apresentam destreza e motivação suficientes para realizar uma correta higienização. Assim, o uso complementar de agentes químicos tem sido estudado como um modo de superar as deficiências na higiene bucal. O objetivo deste trabalho foi apresentar uma revisão sobre o uso de produtos para higiene bucal contendo agentes químicos destinados ao controle da placa bacteriana supragengival. Foram revisados estudos in vitro e ensaios clínicos dos seguintes agentes químicos: clorexidina, óleos essenciais, triclosan, cloreto de cetilpiridínio e novos produtos como delmopinol e dióxido de cloro. Os autores concluem que diversos estudos demonstram a eficácia de enxaguatórios contendo clorexidina e óleos essenciais, assim como dentifrícios contendo triclosan. No entanto, mais estudos são necessários para comprovar a eficácia dos demais agentes químicos.

Detection of herpesviruses and periodontal pathogens in subgingival plaque of patients with chronic periodontitis, generalized aggressive periodontitis, or gingivitis.

BACKGROUND: Herpesviruses may be related to the etiology of aggressive periodontitis (AgP) and chronic periodontitis (CP) by triggering periodontal destruction or by increasing the risk for bacterial infection. This case-control study evaluated the presence of herpes simplex virus type I (HSV-1), Epstein-Barr virus type I (EBV-1), human cytomegalovirus (HCMV), Aggregatibacter actinomycetemcomitans (previously Actinobacillus actinomycetemcomitans), Porphyromonas gingivalis, Prevotella intermedia, and Tannerella forsythia (previously T. forsythensis) in patients with generalized AgP (AgP group), CP (CP group), or gingivitis (G group) and in healthy individuals (C group). METHODS: Subgingival plaque samples were collected with paper points from 30 patients in each group. The nested polymerase chain reaction (PCR) method was used to detect HSV-1, EBV-1, and HCMV. Bacteria were identified by 16S rRNA-based PCR. RESULTS: HSV-1, HCMV, and EBV-1 were detected in 86.7%, 46.7%, and 33.3% of the AgP group, respectively; in 40.0%, 50.0%, and 46.7% of the CP group, respectively; in 53.3%, 40.0%, and 20.0% of the G group, respectively; and in 20.0%, 56.7%, and 0.0% of the C group, respectively. A. actinomycetemcomitans was detected significantly more often in the AgP group compared to the other groups (P <0.005). P. gingivalis and T. forsythia were identified more frequently in AgP and CP groups, and AgP, CP, and G groups had higher frequencies of P. intermedia compared to the C group. CONCLUSION: In Brazilian patients, HSV-1 and EBV-1, rather than HCMV, were more frequently associated with CP and AgP.

Early dental plaque formation on toothbrushed titanium implant surfaces.

PURPOSE: To evaluate the qualitative and quantitative differences on dental plaque formation on two different roughness titanium implant surfaces, i.e. machined and titanium plasma sprayed, as well as the amount of plaque removal by regular toothbrushing after 72-hour plaque accumulation. METHODS: Eight systemically healthy subjects were recruited from the patient pool of a private dental practice. All patients underwent oral hygiene instruction and full mouth prophylaxis. Subsequently, maxillary casts from all patients were obtained and removable 0.7 mm-thick acetate stents without occlusal contact points were fabricated to support four titanium specimens of 4 x 2 x 2 mm divided into two groups (machined and plasma sprayed). Subjects were instructed to wear the stents for 72 hours, full time, removing them only during regular oral hygiene. Subsequently, the appliances were immediately repositioned and then the test side was brushed for 20 seconds. At the end of the 72-hour period, the stents were removed and prepared for microbiological analysis. RESULTS: Both machined and plasma sprayed brushed surfaces presented statistically significant fewer bacteria than non-brushed surfaces. Similarly, regarding surface roughness, machined surfaces presented a total number of bacteria significantly smaller than those presented by plasma sprayed surfaces (P < 0.05). Statistically, the non-brushed machined turned surfaces presented a greater amount of Streptoccocus sp. when compared to the brushed machined surfaces. It was concluded that rough surfaces accumulated more dental plaque than polished surfaces. Both brushed surfaces presented less plaque accumulation, however, implant brushing was more effective on machined surfaces.

Herpes viruses in periodontal compromised sites: comparison between HIV-positive and -negative patients.

AIM: The objective of this study was to compare the frequency of herpes simplex virus type 1 (HSV-1), Epstein-Barr virus (EBV) and human cytomegalovirus (HCMV) in subgingival plaque, saliva and peripheral blood of HIV-positive and-negative patients with periodontal disease. MATERIAL AND METHODS: Fifty HIV-positive subjects (23 with gingivitis, 27 with periodontitis) and 50 healthy HIV-negative patients with chronic periodontitis were included in the study. Parameters of probing depth (PD), clinical attachment level (CAL), gingival index and plaque index were recorded. The samples were processed for viral identification by the nested polymerase chain reaction technique. RESULTS: HCMV was the most prevalent virus in HIV-positive (82%) and-negative patients (84%), and the detection in the three samples was similar (p>0.05). HSV-1 was the least prevalent virus in both groups, being detected in similar frequencies in oral sites and in peripheral blood. EBV-1 was found more frequently in saliva and subgingival plaque of HIV-positive patients than in HIV-negative patients (p< or =0.05). CONCLUSIONS: EBV-1 was more frequently recovered in oral sites of HIV-positive patients than in HIV-negative patients.

Detection of Epstein-Barr virus and human cytomegalovirus in blood and oral samples: comparison of three sampling methods.

The purpose of this study was to identify and compare the presence of HCMV and EBV-1 in subgingival plaque, unstimulated saliva and peripheral blood of patients with chronic periodontitis. Forty patients diagnosed with chronic periodontitis (mean age, 41.7 years) were recruited. Unstimulated saliva, subgingival plaque and peripheral blood were collected from each patient and the DNA of each sample was isolated. The viruses were detected using the nested PCR technique. The detection frequency of EBV-1 in subgingival plaque, saliva and peripheral blood was 45%, 37.5% and 25%, respectively. HCMV was detected in 82.5% of subgingival plaque samples and peripheral blood and in 75% of salivary samples. The sensitivity for detecting EBV-1 in saliva and peripheral blood when EBV-1 was detected in subgingival plaque samples was low (22% and 27.7%, respectively) and the sensitivity for detecting HCMV in saliva and peripheral blood when compared to subgingival plaque was high (81.8% and 87.8%, respectively). There is a high agreement among the three sampling methods in detection of HCMV, but the detection of EBV-1 would require a combination of saliva and subgingival plaque sampling to avoid false negative results.