Visual Evaluation Method Research Articles

Pediatric diffuse intrinsic pontine glioma radiotherapy response prediction: MRI morphology and T2 intensity-based quantitative analyses.

An easy-to-implement MRI model for predicting partial response (PR) postradiotherapy for diffuse intrinsic pontine glioma (DIPG) is lacking. Utilizing quantitative T2 signal intensity and introducing a visual evaluation method based on T2 signal intensity heterogeneity, and compared MRI radiomic models for predicting radiotherapy response in pediatric patients with DIPG. We retrospectively included patients with brainstem gliomas aged ≤ 18 years admitted between July 2011 and March 2023. Applying Response Assessment in Pediatric Neuro-Oncology criteria, we categorized patients into PR and non-PR groups. For qualitative analysis, tumor heterogeneity vision was classified into four grades based on T2-weighted images. Quantitative analysis included the relative T2 signal intensity ratio (rT2SR), extra pons volume ratio, and tumor ring-enhancement volume. Radiomic features were extracted from T2-weighted and T1-enhanced images of volumes of interest. Univariate analysis was used to identify independent variables related to PR. Multivariate logistic regression was performed using significant variables (p < 0.05) from univariate analysis. Of 140 patients (training n = 109, and test n = 31), 64 (45.7%) achieved PR. The AUC of the predictive model with extrapontine volume ratio, rT2SRmax-min (rT2SRdif), and grade was 0.89. The AUCs of the T2-weighted and T1WI-enhanced models with radiomic signatures were 0.84 and 0.81, respectively. For the 31 DIPG test sets, the AUCs were 0.91, 0.83, and 0.81, for the models incorporating the quantitative features, radiomic model (T2-weighted images, and T1W1-enhanced images), respectively. Combining T2-weighted quantification with qualitative and extrapontine volume ratios reliably predicted pediatric DIPG radiotherapy response. Combining T2-weighted quantification with qualitative and extrapontine volume ratios can accurately predict diffuse intrinsic pontine glioma (DIPG) radiotherapy response, which may facilitate personalized treatment and prognostic assessment for patients with DIPG. Early identification is crucial for radiotherapy response and risk stratification in diffuse intrinsic pontine glioma. The model using tumor heterogeneity and quantitative T2 signal metrics achieved an AUC of 0.91. Using a combination of parameters can effectively predict radiotherapy response in this population.

Visual evaluation and information improvement method of smart factory layout based on information value added

Abstract The process of Industry 4.0 is constantly promoted. In order to realize the high-quality connotation development of enterprises, manufacturing enterprises need to carry out information transformation and upgrading. The technology of information flow analysis can consistently assess the worth of the factory, overcome existing technical challenges, and achieve intelligent modernization and enhancement of the system. This study presents a visualization and evaluation of the factory’s layout, production lines, and workstation from three perspectives: macro, meso, and micro. To begin, a value added heat map (VAHM) is created by examining the visualization technique for information value added information (IVA). This analysis aims to assess the extent of information wastage in terms of the factory’s physical space, resources, and staff. Additionally, a method for analyzing the information gain of a production line, which is based on the concept of distributed cognition, is introduced. This method evaluates the production line by integrating the economic principle of information processing (EPIP). Furthermore, when assessing complexity, the volume of information in workstations is measured and enhanced by applying the principle of information processing economy. Ultimately, the method’s validity and feasibility are confirmed by applying it to real-world manufacturing industry scenarios.

Research on digital-visual evaluation method of down fibers odor

Down is often used as a natural filler for warm clothing, but the odor of down is one of the issues that affects the performance of warm clothing applications. At present, the evaluation of down odor mostly uses the human olfactory evaluation method, which has low reproducibility and accuracy. This article first uses the method of activated carbon gas extraction/gas chromatography–mass spectrometry to identify five down odor compounds that can be detected in a stable way, as representative compounds of down odor. Then, a simple direct impregnate extraction/gas chromatography–mass spectrometry method was used to determine the exact concentration of odor compounds in down fibers. Finally, an odor level radar chart was constructed by analyzing the concentration of odor representative compounds of levels 1–5 in down. The digital visual evaluation method was composed of direct impregnate extraction combined with radar chart to judge the down odor level and compared to the human olfactory method. The results indicate that the radar chart evaluation has relatively accurate evaluation results and is more objective and accurate than the human olfactory method. This method for evaluating the odor level of down is simple and reliable, and has certain promotion and application prospects in the down production industry.

Novel collision risk measurement method for multi-ship encounters via velocity obstacles and temporal proximity

The collision risk assessment of multi-ship encounters in busy waters is of great significance for collision risk early warning and the intelligent supervision of maritime traffic. In this paper, a quantitative and visual evaluation method is proposed to describe changes in multi-ship collision risk in the velocity space according to multi-ship collision risk characteristics. Non-linear velocity obstacles and closest point of approach were combined to measure the risk of ship collision from the perspective of both the difficulty and urgency of the encounter. The proposed method was verified via case studies using historical Automatic Identification System data for the East China Sea. The method advantages were confirmed via comparison to the conventional time-varying collision risk and collision risk index methods. The results show that the proposed method can quantify changes in multi-ship collision risk more intuitively and effectively. The proposed method could be further developed as a new risk indicator for maritime traffic safety management and could aid in the navigation safety of manned and unmanned ships.

A Spatial Visual Quality Evaluation Method for an Urban Commercial Pedestrian Street Based on Streetscape Images—Taking Tianjin Binjiang Road as an Example

As core public spaces in cities, urban commercial pedestrian streets are important destinations for local residents and foreign tourists, and confusion regarding the visual space of a commercial pedestrian street sends direct environmental warning signals to pedestrians, affecting their visiting decisions. In this paper, through an investigation consisting of the artificial field simulation of the visual perception of pedestrians, we collect the corresponding street images and extract visual elements using the full convolutional network. Semantic segmentation is performed to obtain the visual parameters of the street. According to the quantitative model, the visual elements are matched with geographic elements, and a geographic information database is established to evaluate the spatial visual quality of commercial pedestrian streets. (1) There is obvious spatial heterogeneity in the spatial visual quality of different streets in commercial pedestrian streets. (2) The building heights, street widths, as well as the street vegetation, facilities, and landscape vignettes are spatial elements that shape the spatial visual quality of commercial pedestrian streets. (3) The main distribution of commercial facilities and the distribution of active businesses have an important impact on the degree of crowd gathering in a street space and the visual spatial quality of a street. This paper provides comparable data collection methods and research methods for the visual spatial quality of commercial pedestrian streets. This paper can also provide valuable data for the design, planning, and sustainable renewal management and regulation of the visual perception of commercial pedestrian streets.

Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning

ObjectiveTo improve the PET image quality by a deep progressive learning (DPL) reconstruction algorithm and evaluate the DPL performance in lesion quantification.MethodsWe reconstructed PET images from 48 oncological patients using ordered subset expectation maximization (OSEM) and deep progressive learning (DPL) methods. The patients were enrolled into three overlapped studies: 11 patients for image quality assessment (study 1), 34 patients for sub-centimeter lesion quantification (study 2), and 28 patients for imaging of overweight or obese individuals (study 3). In study 1, we evaluated the image quality visually based on four criteria: overall score, image sharpness, image noise, and diagnostic confidence. We also measured the image quality quantitatively using the signal-to-background ratio (SBR), signal-to-noise ratio (SNR), contrast-to-background ratio (CBR), and contrast-to-noise ratio (CNR). To evaluate the performance of the DPL algorithm in quantifying lesions, we compared the maximum standardized uptake values (SUVmax), SBR, CBR, SNR and CNR of 63 sub-centimeter lesions in study 2 and 44 lesions in study 3.ResultsDPL produced better PET image quality than OSEM did based on the visual evaluation methods when the acquisition time was 0.5, 1.0 and 1.5 min/bed. However, no discernible differences were found between the two methods when the acquisition time was 2.0, 2.5 and 3.0 min/bed. Quantitative results showed that DPL had significantly higher values of SBR, CBR, SNR, and CNR than OSEM did for each acquisition time. For sub-centimeter lesion quantification, the SUVmax, SBR, CBR, SNR, and CNR of DPL were significantly enhanced, compared with OSEM. Similarly, for lesion quantification in overweight and obese patients, DPL significantly increased these parameters compared with OSEM.ConclusionThe DPL algorithm dramatically enhanced the quality of PET images and enabled more accurate quantification of sub-centimeters lesions in patients and lesions in overweight or obese patients. This is particularly beneficial for overweight or obese patients who usually have lower image quality due to the increased attenuation.

Research on Visual Quality Evaluation Method of Tourist Highway Based on Virtual Driving

This paper studies the visual quality evaluation method along the tourist highway from the driver’s first perspective, selects five evaluation indexes from the aspects of driver’s driving reaction and physiological reaction, and establishes a “man-vehicle-road” visual quality evaluation method model of tourist highway. Through BIM + VR technology, the tourist highway scene is built for virtual driving experience and evaluation, and different landscape design schemes and dynamic effects of tourist highway are reproduced virtually. Combined with questionnaire survey and physiological data feedback, the tourist highway landscape is evaluated qualitatively and quantitatively, and a qualitative and quantitative evaluation method for the visual quality of tourist highway is put forward. It provides decision-making basis for local relevant departments to carry out landscape design quality evaluation along tourist highways, and realizes high-quality development of tourist highways.

Research on Visual and Interactive Evaluation Methods for Space Design Based on Virtual Reality Technology

Abstract This paper establishes different detail-level terrain grids for different terrain data blocks and generates multi-resolution terrain based on the tree-structured LOD model as a way of layering large-scale terrain data. Then, the virtual environment’s visual and image texture are rendered to visualize the virtual spatial environment. Then, the overall architecture of the interaction platform was designed, and the virtual space design visualization and interaction effects were studied based on spatial distance perception, presence experience perception, and error analysis. The results show that there is a significant difference between the mean value of people’s perceived satisfaction in the interaction space and non-interaction space M=163.138, t=1.376, p=0.005&lt;0.05. The error in the interaction of the system in this paper is between (0.2 and 1.8), which indicates that the system performs well. This study of interaction design research proposes a new research dimension for the traditional interaction interface based on virtual reality technology, which provides an effective reference basis for future related designs.

Research on Product Model Generation and Visual Presentation Incorporating Computational Aesthetics

Abstract In the era of aesthetic economy, users pay more and more attention to the aesthetic quality and emotional experience of products. The study discusses the intelligent design method of product model integrating computational aesthetics, combines the advantages of variational self-encoder and generative adversarial network, constructs a generative model based on VAE-GAN, and quantitatively analyzes the product images generated by the VAE-GAN network to explore the effect of the products it generates. Then, take the car form generated by the model as an example, establish the visual presentation quantitative index system of the product model form layout, and evaluate the visual presentation effect of the generated car model after applying gray correlation analysis to assign the indexes. The VAE-GAN model has a better generative effect, and its SSIM value is greater than 0.8 in most of the training phases. Among them, the product model generated after 2000 steps of training is the most excellent, with the highest evaluation score. The product model is the most outstanding, with the highest evaluation score of 1.92. The overall visual presentation effect of the product forms generated by the model is good, and the comprehensive evaluation scores are above 0.6. The VAE-GAN model can be used for product generation, and the visual presentation evaluation method that integrates computational aesthetics can realize the aesthetic evaluation of product forms, which can help designers make design creations and program decisions.

Construction of a cultural image visual perception and aesthetic model based on a deep learning algorithm

This article studies the perceptual quality evaluation method of humanistic images based on the characteristics of human vision. First, this study obtained the disparity map of the human visual cultural image and used the edge map and saliency map to correct the weight of the disparity map. The weighted disparity map was then integrated into a perceptible score using a Minkowski fused deep neural network. A multi-scale method was employed to process the image to obtain the visual effect score. Taking Polytechnic University of Lausanne (EPFL) as an example, an experimental study was conducted on the three dimensional visual quality assessment method proposed in this article. The test results with the EPFL library show that the target score obtained by this method has good consistency and monotonicity with the subjective score of the EPFL library. The article's results verify the effectiveness of the visual effects and aesthetics evaluation method proposed in this article.

Assessing soil structural quality as an indicator of productivity under semi-arid climate

A near real-time evaluation of the management system's impact on soil conditions requires a quick and straightforward framework to help farmers with a reliable on-farm assessment. The visual soil evaluation methods can potentially be used as a reliable on-farm approach for assessing soil physical quality. This research aims to better understand the importance of visual soil evaluation for productivity in semi-arid climates. The objectives were to evaluate the ability of Visual Evaluation of Soil Structure (VESS) and Double Spade (DS) under agricultural systems in a semi-arid region and to assess the relationship between soil structural quality and crop yield. Forty arable sites under rain-fed and irrigated farming with crop rotation and mono-cropping systems were studied, and twenty-one physical and bio-chemical soil properties were determined at two depths (0–20 cm and 20–40 cm). VESS and DS were conducted at each farm. The reliability of visual approaches was evaluated using measured soil properties and their capability to detect the impact of management systems. Soil quantitative measurements and crop yield information were deployed to assess soil productivity and its relationship with soil physical quality. The overall assessment of soil properties indicated a better soil condition for irrigated farming with crop rotation. The visual scores were in a range of 1.5–3.4 for VESS and a range of 1.9–3.5 for DS. The mean scores of VESS and DS were different between rain-fed and irrigated farms (P < 0.05), and visual methods were able to differentiate between mono-cropping and crop rotation (P < 0.05). The best soil structural quality was associated with the highest level of crop yield, and visual approaches were able to detect the differences in wheat yield levels (P < 0.05). The scores of VESS and DS were significantly correlated with soil properties (r > 0.6). Both VESS and DS indicated good efficiency for a practical on-farm assessment of soil conditions under agricultural management in northwest Iran and similar ecosystems. A close relationship between crop yield and soil structural quality was obtained, which indicated that the optimum soil structural condition plays an important role in the sustainability of crop production in semi-arid cultivation.

Significance of the Goddard Score in Predicting Complications Related to Air Leak After Lobectomy

BackgroundPostoperative air leakage is a frequent complication after lung resection, and emphysema is a risk factor. However, no study has investigated the relationship between emphysema severity and postoperative complications related to air leak by the Goddard score (GS), a visual evaluation method of radiologic emphysema using computed tomography. MethodsThis study included patients who underwent lobectomy for non-small cell lung cancer between April 2009 and March 2022. The utility of GS in predicting complications related to air leak (air leak prolonged for ≥5 days, pleurodesis, and reoperation for air leak) was investigated by receiver operating characteristic curve analysis and multivariable analysis with a logistic regression model. ResultsThis study included 477 patients. The GS was a significant predictor of complications related to air leak (area under the curve, 0.696; P < .001). Based on the receiver operating characteristic curve analysis, GS of 6 points was used as the cutoff point for multivariable analysis. In the multivariable analysis, GS of ≥6 points was a significant predictor of complications related to air leak (odds ratio, 2.719; P = .007). In the subgroup analysis of patients with emphysema, GS of ≥6 points was a significant predictor of complications related to air leak (P = .014). ConclusionsThe GS was useful in predicting complications related to air leak. Patients with radiologic findings of emphysema with GS of ≥6 points should be recognized as a high-risk group for complications related to air leak.

Multi-scale feature fusion-based lightweight dual stream transformer for detection of paddy leaf disease.

Traditionally, rice leaf disease identification relies on a visual examination of abnormalities or an analytical result obtained by growing bacteria in the research lab. This method of visual evaluation is qualitative and error-prone. On the other hand, an artificial neural network system is fast and more accurate. Several pieces of research using traditional machine learning and deep convolution neural networks (CNN) have been utilized to overcome the issues. Still, these methods need more semantic contextual global and local feature extraction. Due to this, efficiency is less. Hence, in the present study, a multi-scale feature fusion-based RDTNet has been designed. The RDTNet contains two modules, and the first module extracts feature via three scales from the local binary pattern (LBP), gray, and a histogram of orient gradient (HOG) image. The second module extracts semantic global and local features through the transformer and convolution block. Furthermore, the computing cost is reduced by dividing the query into two parts and feeding them to convolution and the transformer block. The results indicate that the proposed method has a very high average precision, f1-score, and accuracy of 99.55%, 99.54%, and 99.53%, respectively. It is suggestive of improved classification accuracy using multi-scale features and the transformer. The model has also been validated on other datasets confirming that the present model can be used for real-time rice disease diagnosis. In the future, such models can be used for monitoring other crops, including wheat, tomato, and potato.

Visual art evaluation methods in future digital works: From virtual reality to metaverse

The motivation for this paper is to consider that in recent years, the concept of metaverse, as the latest and most popular concept in the world, has been widely applied and studied in various industries, including economic management, art design, education and teaching. However, the academic and scientific circles have not reached a consensus on whether to define the metaverse as a technology or an intelligent scene. We believe that the metaverse should be a key concept and emerging theory for constructing the future wisdom field. Therefore, in this study, our research objective is to focus on the visual art evaluation in digital works, and propose a visual art quality evaluation method in future metaverse digital works. This method is based on the quality function deployment theory and fuzzy mathematics theory in marketing. The second core point of this study is to build a field framework for the visual art evaluation of future digital works based on the metaverse by combing the current international and domestic understanding of the concept of metaverse. In addition, taking visual art quality evaluation as the research object, we have constructed a visual art quality evaluation index system for digital works under the background of metaverse. The index system is composed of one first-class index, three second-class indexes and nine third-class indexes. At the same time, we proposed a new fuzzy mathematics evaluation method in the research, called G1 entropy method. This algorithm combines subjective weighting method: G1 method and objective weighting method: entropy method as an important method of quality evaluation, and carries out the final rating through the combination weight of G1 entropy method. This study makes up for the concept of the future metaverse, introduces the gaps in the theory of visual art evaluation of future digital works, innovates the analysis of new concepts and the improvement of old methods, builds a new scene of organic combination of new technology and traditional visual art, and provides new ideas for the improvement of art quality at home and abroad in the future. In general, we sorted out the contributions of this research, including the following three aspects: (1) we constructed the metaverse field structure of digital works. By analyzing the current international and domestic research literature on the application of metaverse technology, especially the concept of metaverse in art scenes, we proposed to construct the field structure of online visual art after introducing the concept of metaverse, including blockchain technology, artificial intelligence technology Interaction technology and Internet of things technology as the four characteristics; (2) Method theoretical contribution: we further take the visual art quality evaluation as the research object, construct the index system of visual art quality evaluation of digital works under the background of metaverse, and propose an evaluation method of G1 entropy method, which is actually a method of subjective weighting by experts; (3) We use the method proposed in (2) to complete the calculation and ranking of the importance of 9 indicators in a practical case, and give some countermeasures for the calculation results of the importance of indicators. In conclusion, this study has realized the construction of new application scenarios of concepts and the new improvement of methods, and can provide theoretical and practical case experience support for the quality improvement of international and domestic metaverse visual art.

Research on Green Consumption Based on Visual Evaluation Method—Evidence from Stone Flooring Industry

Blind consumption discovered in the real application of flooring does not produce the visually anticipated impression, leading to additional time costs and stone flooring waste. Consumers cannot clearly articulate their visual imaging needs when purchasing stone flooring. Due to consumers’ lack of understanding of the visual imagery style of decorative stone flooring, manufacturers are unable to produce more visual styles of stone flooring in response to consumer demand, which leads to an unorganized production process and the wasting of stone resources. Additionally, manufacturers are unable to receive feedback on market demand, which makes communication links between sales teams difficult. A total of 40 adjectives were considered the most appropriate in a pool of 110 adjectives for the visual imagery evaluation of stone after ten interior design professionals with experience in decorative stone applications had narrowed the selection. Following this, a general consumer semantic difference method questionnaire survey and questionnaire data factor analysis statistics were used to create 10 sets of visual imagery adjectives for marble flooring, which were then divided into 10 different types of marble flooring. Following the computer simulation drawing with the 10 groups of visual imagery adjectives design questionnaire, the consumers completed the visual imagery evaluation questionnaire survey. They received a 304-question valid questionnaire, and using the triangular fuzzy number operation in fuzzy theory, they arrived at 10 marble floors in the visual imagery evaluation score. In order to clarify the current consumer demand for stone floor imagery, the high sales volume of stone flooring on the market for visual style division, which can guide consumers according to their visual needs for an efficient choice, can enhance the efficiency of communication between consumers and sellers. It can also help enterprises clarify the market consumer demand for orderly production to achieve the purpose of green consumption and to ensure the sustainable development of the decorative stone flooring market.

Identification of important terraced visual landscapes based on a sensitivity-subjectivity preference matrix for agricultural cultural heritage in the southwestern china

Landscapes illustrating agricultural cultural heritage can serve as an important attraction to encourage tourism in support of rural revitalization in mountainous areas. These landscapes can aid in clarifying the regional scale of agricultural areas and identifying the visual landscape resources that play an important role in promoting the rational and sustainable use and development of resources in mountainous landscapes. Taking the terraced agricultural landscape with cultural resources in the southwestern mountainous region of China as the research object, a landscape visual sensitivity analysis was conducted on this region. This was done using GIS spatial analysis based on the data of relative slope, relative distance, and occurrence probability in the region and scenic beauty evaluation based on 176 questionnaires. Based on the importance-performance analysis, a sensitivity-subjectivity preference matrix of the visual landscape of having terraced agricultural and heritage resources in the southwestern mountainous area of China was constructed. Next, the visual landscape in the study area was classified into four types of areas, and corresponding landscape protection and planning suggestions were proposed. The study shows that the villages of Liushe, Qinglong, and Jiupang are in the “critical visual landscape area” and are evaluated as having high sensitivity-high preference evaluation; the villages of Baidu and Bailu are in the “natural development area” with low sensitivity-high preference. Furthermore, Zhanliu village is in the “priority improvement area” with high sensitivity-low preference; lastly, the villages of Jiulong, Liuzhai, and Liufu are in the “second priority improvement zone” with low sensitivity and preference. The findings of this study can provide a reference for determining the timing and direction of landscape development of agricultural heritage in the terraced mountainous areas of southwestern China; the landscape visual evaluation method employed here has implications for the identification of key areas in other mountainous landscapes.

광학적 특성 평가기법을 이용한 지문현출 시약 1,2-IND와 BY40의 광발광 모드 최적조건에 대한 연구

Fingerprints are formed on various surfaces in crime scenes. Cyanoacrylate fuming with Basic Yellow 40 is usually used on non-porous surfaces and 1,2-Indanedione is the most common reagent for developing latent fingerprints. In general, developed fingerprints are observed using a light source and filter within corresponding wavelength range. This observation technique is called photoluminescence mode. Since the photoluminescence mode uses light sources and filters in the darkroom, it is easy to observe only the developed fingerprints. Therefore, many studies have been conducted to find best filter and light combination of latent fingerprint development reagents. But most of the studies on optimal photoluminescence conditions were based on visual evaluation methods such as the Home Office Grading System or SWGFAST. Since these visual evaluation criteria are based on the evaluator's visual judgment, the results may vary depending on the evaluator's competency, and it is difficult to compare if the difference in the degree of enhancement and appearance is small. To solve this problem, this study aims to quantify the quality of fingerprints and establish the optimal conditions for fingerprint development reagent(1,2-Indanedione, Basic Yellow 40) commonly used on porous and non-porous surfaces. Evaluation factors were set as optical characteristics that can affect the evaluation of the fingerprint, referring to previous studies. Brightness, contrast, signal to noise ratio were set as evaluation factors. More detailed comparison was possible using the optical characteristic evaluation technique, and the optimal light source and filter conditions according to the reagent could be found.

Diagnostic Accuracy of MRI Evaluation of Patellar Position According to the Physeal Line in Pediatric Patients

Aim: Abnormal positioning of the patella, of which the superior position is defined as patella alta (PA), whereas the inferior position is defined as patella baja (PB). Most of the measurements of patellar position evaluations are time-consuming. In this study, we aimed to examine the diagnostic accuracy of visual evaluation of the patellar position according to the physeal line and to determine the inter- and intraobserver agreement of this evaluation in MRI examinations. Material and Methods: Knee MRI examinations performed between 2019-2021 with different knee symptoms and prediagnoses were retrospectively analyzed in this study. As a reference test, Insall-Salvati Ratio was calculated by the following formula: Tendon length/patellar length. Two visual evaluation methods were used; physis line to the patella (PLP) and physis line to patellar joint cartilage (PLC). Results: Three hundred and sixty consecutive children aged 60-215 months were included in the study. There was excellent an agreement of both intra- and interobserver on PLP and PLC for two observers (κ &amp;gt; 0.800, for all). When we evaluated intra- and interobserver agreements according to groups, almost perfect agreements were detected (κ &amp;gt; 0.750, for all). Diagnostic accuracy for both two observers on the visual evaluation of PLP was almost perfect (Sensitivity 95.5%, specificity 87.2% for observer 1, and Sensitivity 94.7%, specificity 87.2% for observer 2), and on the PLC evaluation was also good (Sensitivity 89.3%, specificity 82.9% for observer 1, and Sensitivity 88.1%, specificity 85.5% for observer 2). Conclusion: Even though direct radiography is used in the diagnosis of PA and PB, it has been shown that MRI can also be used in pediatric patients in daily practice. Instead of the time-consuming measurements used in MRI, it may be kept in mind to use these methods in our study for practical and accurate diagnosis.

The influence of interradicular anatomy on the predictability of periodontal regenerative therapy of furcation defects: a retrospective, multicenter clinical study

BackgroundThe relationship between the anatomy of the interradicular space and success in regenerative therapy of furcation defects is discussed in this paper. The goal of this retrospective, multicenter clinical study is to clinically evaluate the relationship between the interradicular conformation and regenerative therapy success with the use of a novel measurement method.MethodsOne hundred thirty-eight radiographs of mandibular molars with furcation defects that had been treated with regenerative therapy were collected from six clinical centers. Data on the type of therapy and clinical parameters before and after treatment (follow-up of at least 12 months) were collected. The radiographs (before surgery and at least 12 months postoperatively) were measured with a visual evaluation method by a blind operator using graphics software.ResultsSuccess, defined as a reduction in horizontal and vertical furcation involvement, decrease in probing depths, and increase in clinical attachment level, was statistically assessed on 138 regenerated molars sites and were related to clinical variables such as age, sex, center, and treatment. No correlation was found between success in regenerative therapy and the conformation of the interradicular space, measured with a visual ratio method and a standard linear measurement.At the univariate analysis, the parameters that had a correlation with success were center, extent of furcation involvement, treatment, and sex. The use of enamel matrix derivative (EMD) seemed to be the most favorable therapy, with increase in CAL gain and reduction of vertical or horizontal furcation involvement.ConclusionsThe regenerative outcome was not significantly influenced by the anatomy of furcation. The center, the degree of furcation involvement, sex, and treatment (EMD) were significantly associated with higher success of periodontal regeneration.

Radiographic ratios for classifying furcation anatomy: proposal of a new evaluation method and an intra-rater and inter-rater operator reliability study

ObjectivesEven if it seems to be an important anatomical parameter for tissue regeneration, few studies in literature evaluate the “mean measure” of root divergence. Most of them are linear measurements, which hardly describe the dental furcation conformation in its entirety. It is left to the subjectivity of the operator deciding whether a furcation is convergent or divergent. The goal of this study is to create a visual evaluation method using specific measurements applied on endo-oral X-rays to overcome these problems, giving a conformation of the entire interradicular space and its divergence.Material and methodsA user-friendly software (Paint®, Windows10®) was used to take three different measurements on endo-oral radiographs of upper and lower molars. Three blind operators measured 20 radiographs, to analyze the intra- and inter-operator reproducibility of the measurements. Then, the technique was repeated on 250 radiographic images to identify an average value and define a main conformation of the interradicular space. The ratio of these three measurements allowed to develop a new visual evaluation method of the interradicular space.ResultsIntra and inter-operator reproducibility was statistically confirmed on a sample of 20 anonymous endo-oral radiographs measured by 3 blind operators, indicating that the measurement technique was not operator dependent. Measurement made on 250 X-rays obtained with this technique permitted to subdivide in five groups the conformation of the interradicular space and define a mean value of the interradicular space.ConclusionsA new anatomical evaluation of the interradicular space in its entirety, which could help the clinicians in diagnostic and decisional phase in the therapy of furcated molars, can be obtained.Clinical relevanceA pre-operative evaluation of interradicular space conformation could affect therapy treatment choice.