Intraoperative margin assessment during radical prostatectomy: is microscopy frozen in time or ready for digital defrost?

Intraoperative frozen section (IFS) is used with the intention to improve functional and oncological outcomes for patients undergoing radical prostatectomy (RP). High resource requirements of IFS techniques such as NeuroSAFE may preclude widespread adoption, even if there are benefits to patients. Recent advances in fresh-tissue microscopic digital imaging technologies may offer an attractive alternative, and there is a growing body of evidence regarding these technologies. In this narrative review, we discuss some of the familiar limitations of IFS and compare these to the attractive counterpoints of modern digital imaging technologies such as the speed and ease of image generation, the locality of equipment within (or near) the operating room, the ability to maintain tissue integrity, and digital transfer of images. Confocal laser microscopy (CLM) is the modality most frequently reported in the literature for margin assessment during RP. We discuss several imitations and obstacles to widespread dissemination of digital imaging technologies. Among these, we consider how the 'en-face' margin perspective will challenge urologists and pathologists to understand afresh the meaning of positive margin significance. As a part of this, discussions on how to describe, categorize, react to, and evaluate these technologies are needed to improve patient outcomes. Limitations of this review include its narrative structure and that the evidence base in this field is relatively immature but developing at pace.

Digital pathology for reporting histopathology samples, including cancer screening samples - definitive evidence from a multisite study.

AIMS: To conduct a definitive multicentre comparison of digital pathology (DP) with light microscopy (LM) for reporting histopathology slides including breast and bowel cancer screening samples. METHODS: A total of 2024 cases (608 breast, 607 GI, 609 skin, 200 renal) were studied, including 207 breast and 250 bowel cancer screening samples. Cases were examined by four pathologists (16 study pathologists across the four speciality groups), using both LM and DP, with the order randomly assigned and 6 weeks between viewings. Reports were compared for clinical management concordance (CMC), meaning identical diagnoses plus differences which do not affect patient management. Percentage CMCs were computed using logistic regression models with crossed random-effects terms for case and pathologist. The obtained percentage CMCs were referenced to 98.3% calculated from previous studies. RESULTS: For all cases LM versus DP comparisons showed the CMC rates were 99.95% [95% confidence interval (CI) = 99.90-99.97] and 98.96 (95% CI = 98.42-99.32) for cancer screening samples. In speciality groups CMC for LM versus DP showed: breast 99.40% (99.06-99.62) overall and 96.27% (94.63-97.43) for cancer screening samples; [gastrointestinal (GI) = 99.96% (99.89-99.99)] overall and 99.93% (99.68-99.98) for bowel cancer screening samples; skin 99.99% (99.92-100.0); renal 99.99% (99.57-100.0). Analysis of clinically significant differences revealed discrepancies in areas where interobserver variability is known to be high, in reads performed with both modalities and without apparent trends to either. CONCLUSIONS: Comparing LM and DP CMC, overall rates exceed the reference 98.3%, providing compelling evidence that pathologists provide equivalent results for both routine and cancer screening samples irrespective of the modality used.

Excellent accuracy of trained neonatal nurses in the detection of referral-warranted retinopathy of prematurity within an established telemedicine screening programme.

AIM: To evaluate level of agreement of specialist trained retinopathy of prematurity (ROP) nurses compared with an experienced paediatric ophthalmologist in detection of referral-warranted ROP (RWROP) using wide-field digital retinal imaging. METHODS: This is a prospective, observational, blinded study of neonates in a level III neonatal intensive care unit, from July 2020 to November 2022. Image capture using wide-field digital retinal imaging followed by ROP grading and staging was completed by trained ROP nurses. This was then compared with findings by an experienced paediatric ophthalmologist. The primary outcome was presence of RWROP in either eye. RESULTS: One hundred and ninety-five neonates (55% male) with a total of 768 screening visits were included. At the initial screen, nurse and ophthalmologist agreed about presence of RWROP for 191 of 195 neonates (98%, kappa = 0.79, P < 0.0001), with 100% sensitivity for RWROP detection. Including all 768 screening episodes, agreement was 98% for RWROP. There was disagreement in 16 screenings (2%) for 11 (6%) neonates. Of the five screenings (0.7%) that the ophthalmologist thought were RWROP and the nurse did not, three were disagreements about whether the zone was posterior zone 2 or zone 1. CONCLUSIONS: We found excellent levels of agreement and add evidence that interpretations by specialist trained nurses could be safely integrated into a 'hybrid ROP screening system'.

Machine learning-based medical imaging diagnosis in patients with temporomandibular disorders: a diagnostic test accuracy systematic review and meta-analysis.

OBJECTIVES: Temporomandibular disorders (TMDs) are the second most common musculoskeletal condition which are challenging tasks for most clinicians. Recent research used machine learning (ML) algorithms to diagnose TMDs intelligently. This study aimed to systematically evaluate the quality of these studies and assess the diagnostic accuracy of existing models. MATERIALS AND METHODS: Twelve databases (Europe PMC, Embase, etc.) and two registers were searched for published and unpublished studies using ML algorithms on medical images. Two reviewers extracted the characteristics of studies and assessed the methodological quality using the QUADAS-2 tool independently. RESULTS: A total of 28 studies (29 reports) were included: one was at unclear risk of bias and the others were at high risk. Thus the certainty of evidence was quite low. These studies used many types of algorithms including 8 machine learning models (logistic regression, support vector machine, random forest, etc.) and 15 deep learning models (Resnet152, Yolo v5, Inception V3, etc.). The diagnostic accuracy of a few models was relatively satisfactory. The pooled sensitivity and specificity were 0.745 (0.660-0.814) and 0.770 (0.700-0.828) in random forest, 0.765 (0.686-0.829) and 0.766 (0.688-0.830) in XGBoost, and 0.781 (0.704-0.843) and 0.781 (0.704-0.843) in LightGBM. CONCLUSIONS: Most studies had high risks of bias in Patient Selection and Index Test. Some algorithms are relatively satisfactory and might be promising in intelligent diagnosis. Overall, more high-quality studies and more types of algorithms should be conducted in the future. CLINICAL RELEVANCE: We evaluated the diagnostic accuracy of the existing models and provided clinicians with much advice about the selection of algorithms. This study stated the promising orientation of future research, and we believe it will promote the intelligent diagnosis of TMDs.

An Online Digital Imaging Excitation Sensor for Wind Turbine Gearbox Wear Condition Monitoring Based on Adaptive Deep Learning Method.

This paper designed and developed an online digital imaging excitation sensor for wind power gearbox wear condition monitoring based on an adaptive deep learning method. A digital imaging excitation sensing image information collection architecture for magnetic particles in lubricating oil was established to characterize the wear condition of mechanical equipment, achieving the real-time online collection of wear particles in lubricating oil. On this basis, a mechanical equipment wear condition diagnosis method based on online wear particle images is proposed, obtaining data from an engineering test platform based on a wind power gearbox. Firstly, a foreground segmentation preprocessing method based on the U-Net network can effectively eliminate the interference of bubbles and dark fields in online wear particle images, providing high-quality segmentation results for subsequent image processing, A total of 1960 wear particle images were collected in the experiment, the average intersection union ratio of the validation set is 0.9299, and the accuracy of the validation set is 0.9799. Secondly, based on the foreground segmentation preprocessing of wear particle images, by using the watered algorithm to obtain the number of particles in each size segment, we obtained the number of magnetic particle grades in three different ranges: 4-38 µm, 39-70 µm, and >70 µm. Thirdly, we proposed a method named multidimensional transformer (MTF) network. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are used to obtain the error, and the maintenance strategy is formulated according to the predicted trend. The experimental results show that the predictive performance of our proposed model is better than that of LSTM and TCN. Finally, the online real-time monitoring system triggered three alarms, and at the same time, our offline sampling data analysis was conducted, the accuracy of online real-time monitoring alarms was verified, and the gearbox of the wind turbine was shut down for maintenance and repair.

Evaluation of near-infrared digital imaging transillumination compared with bitewing radiography for proximal caries detection in children.

BACKGROUND: Limitations in traditional caries detection tools have driven the development of alternatives methods, focused on the early lesion detection such as near-infrared digital imaging transillumination (NIDIT). AIM: The aim of this study was to evaluate the performance of NIDIT compared with bitewing radiography (BWR) in the detection of interproximal carious lesions in children. DESIGN: A retrospective audit of data from children who had NIDIT, BWR and intraoral photographs was conducted. Carious lesions were scored on a tooth surface level with BWR acting as the primary reference for comparison. Accuracy was determined using multi-class area under the curve (AUC), and correlation was determined using Fleiss' Kappa. RESULTS: Data from 499 tooth surfaces involving 44 children were included in this study. The average age across the participants was 86 months (~7 years) with an average dmft (decayed, missing and filled teeth in primary dentition) of 5.29. Multi-class AUC comparing NIDIT to BWR was 0.70. The correlation between NIDIT and BWR was moderate (0.43), whereas the correlation between photographic examination and BWR was 0.30, which is fair. CONCLUSION: When compared to BWR, NIDIT showed a high specificity but a low sensitivity for proximal caries detection in primary teeth.

Patients' Perspective On The Inclusion Of Intraoral Scanners In Routine Examination: A Clinical Perception Study.

PURPOSE: Is to investigate how integrating intraoral scanners in routine oral diagnosis affects patient-clinician communication, patient perceptions and preferences, offering valuable insights into the patient experience and utility of intraoral scanners in clinical practice. MATERIALS AND METHODS: A restorative dentistry specialist conducted intraoral examination on 300 patients, initially using conventional techniques and X-rays, followed by a 3D scanner (ITero®element, Align Technologies, San Jose, California, USA). The patient's existing oral issues and treatment plan were initially expressed verbally, and then repeated using a 3D scan. Subsequently, the patients were requested to respond to an 11-question survey, aimed at assessing both modes of examination and communication. Statistical analysis using SPSS v.22 software included employing the Wilcoxon test to compare the patients' experiences on the same topic before and after the examination with the intraoral scanners, considering significance at p<0.05. RESULTS: Majority (38%) of participants aged 25-35. Gender split was 52% female, 48% male. Patients statistically found it more comprehensible to visualize existing oral issues through 3D scans than through verbal explanation (p=0.000). Also, patients understood oral hygiene recommendations better when explained via 3D scanning by dentists (p=,000). The vast majority of the participants (94%) indicated that being examined with an intraoral scanner motivated them for treatment, while 6% remained undecided. A hundred percent of the participants stated that 3D scanners should be included in the routine oral examination. CONCLUSION: Intraoral 3D scans enhance patient understanding and communication during oral examination and participants show high preference. However, more research needed to replace conventional diagnostic methods.

A simple, fast, and cost-effective smartphone-based digital imaging method for quantification of lidocaine hydrochloride in pharmaceutical formulations.

OBJECTIVE: A simple, highly specific, accurate and fast method by smartphone-based digital imaging was developed for estimating lidocaine hydrochloride in pharmaceutical formulations. MATERIAL AND METHODS: To obtain the images, a Galaxy A03 Core smartphone and an image acquisition device developed in the laboratory were used to control the incident factors in reproducibility of the measurements. The processing of the images was carried out with the Color Grab application. Finally, the absorbance values were calculated using the RGB intensity values of blank, standard, and sample solutions. The proposed method was compared with spectroscopic and chromatographic methods. RESULTS: The reaction between copper and lidocaine hydrochloride was characterized, showing better results in an equimolar ratio and maintaining the pH of the solution above 11.5. The use of the device for the capture of digital images allowed to control those sensitive parameters for reproducibility so that the analytical measurements showed adequate precision and accuracy. Validation of the main parameters of the method showed compliance with acceptance criteria. The application of the method for the analysis of injectable samples achieved reliable results, which were statistically similar to other reference instrumental methods. CONCLUSION: The proposed method presented figures of merit in relation to linearity, precision, selectivity, accuracy, and robustness; it was carried out by designing and manufacturing a device for capturing digital images on a smartphone, which were analyzed to obtain RGB intensity values. These data are finally used to calculate absorbance values of solutions. All these elements provide this work with innovative characteristics in the field of analysis for control of pharmaceutical formulations.

Confocal laser microscopy for assessment of surgical margins during radical prostatectomy.

OBJECTIVE: To evaluate the feasibility of confocal laser microscopy (CLM) for intraoperative margin assessment as faster alternative to neurovascular structure-adjacent frozen-section examination (NeuroSAFE) during robot-assisted radical prostatectomy (RARP). PATIENTS AND METHODS: Surgical margins were assessed during 50 RARP procedures in patients scheduled for NeuroSAFE. Posterolateral sections were cut and imaged with CLM and further processed to conform with the NeuroSAFE protocol. Secondary resection (SR) was performed in case a positive surgical margin (PSM) was observed with NeuroSAFE. Afterwards, the CLM images were non-blinded assessed for the presence of PSMs. The accuracy of both NeuroSAFE and CLM was compared with conventional histopathology. Agreement for detection of PSMs between NeuroSAFE and CLM was evaluated with Cohen's kappa coefficient. Procedure times were compared with a Wilcoxon signed-ranks test. RESULTS: In total, 96 posterolateral sections of RP specimens were evaluated for the presence of PSMs. CLM identified 15 (16%) PSMs and NeuroSAFE identified 14 (15%) PSMs. CLM had a calculated sensitivity, specificity, positive predictive value and negative predictive value of 86%, 96%, 80% and 98% respectively for the detection of PSMs compared to definite pathology. After SR, residual tumour was found in six of 13 cases (46%), which were all identified by both techniques. There was a substantial level of agreement between CLM and NeuroSAFE (κ = 0.80). The median procedure time for CLM was significantly shorter compared to NeuroSAFE (8 vs 50 min, P < 0.001). The main limitation of this study was the non-blinded assessment of the CLM images. CONCLUSIONS: Compared to NeuroSAFE, CLM is a promising technique for intraoperative margin assessment and is able to reduce the time of intraoperative margin assessment.

Effect of periodontal phenotype characteristics on post-extraction dimensional changes of the alveolar ridge: A prospective case series.

AIM: This study was primarily aimed at assessing the effect that specific periodontal phenotypical characteristics have on alveolar ridge remodelling after tooth extraction. MATERIALS AND METHODS: Patients in need of extraction of a non-molar maxillary tooth were enrolled. Baseline phenotypical characteristics (i.e., mid-facial and mid-palatal soft tissue and bone thickness, and supracrestal soft tissue height [STH]) were recorded upon extraction. A set of clinical, digital imaging (linear and volumetric), and patient-reported outcomes were assessed over a 14-week healing period. RESULTS: A total of 78 subjects were screened. Forty-two subjects completed the study. Linear and volumetric bone changes, as well as vertical linear soft tissue and alveolar ridge volume (soft tissue contour) variations, were indicative of a marked dimensional reduction of the alveolar ridge over time. Horizontal facial and palatal soft tissue thickness gain was observed. Thin facial bone (≤1 mm) upon extraction, compared with thick facial bone (>1 mm), was associated with greater linear horizontal (-4.57 ± 2.31 mm vs. -2.17 ± 1.65 mm, p = .003) and vertical mid-facial (-0.95 ± 0.67 mm vs. -4.08 ± 3.52 mm, p < 0.001) and mid-palatal (-2.03 ± 2.08 mm vs. -1.12 ± 0.99 mm, p = 0.027) bone loss, as well as greater total (-34% ± 10% vs. 15% ± 6%, p < 0.001), facial (-51% ± 19% vs. 28% ± 18%, p = 0.040), and palatal bone volume reduction (-26% ± 14% vs. -8% ± 10%, p < 0.001). Aside from alveolar bone thickness, STH was also found to be a predictor of alveolar ridge resorption since this variable was directly correlated with bone volume reduction. Patient-reported discomfort scores progressively decreased over time, and the mean satisfaction upon study completion was 94.5 ± 0.83 out of 100. CONCLUSIONS: Alveolar ridge remodelling is a physiological phenomenon that occurs after tooth extraction. Post-extraction alveolar ridge atrophy is more marked on the facio-coronal aspect. These dimensional changes are more pronounced in sites exhibiting a thin facial bone phenotype (Clinicaltrials.gov NCT02668289).

Validity and Reliability of Two Digital Wound Measurement Tools after Surgery in Patients with Hidradenitis Suppurativa.

BACKGROUND: After excision surgery in patients with hidradenitis suppurativa (HS), wounds are usually left open for secondary intention healing. To evaluate wound healing, reliable wound measurement is important. However, digital wound measurement tools for measuring the surface area are validated for small wounds located on flat or mildly convex body surfaces in studies, often powered inadequately. Up until now, a validated digital measurement tool to accurately measure wounds on all body surfaces, including the intertriginous areas, was not available. OBJECTIVES: The aim of this study was to validate two digital wound measurement tools for the measurement of the surface area of larger and concave wounds, using surgical wounds in patients with HS. METHODS: This prospective observational validation study included consecutive patients with HS undergoing excision surgery in the Department of Dermatology of the Erasmus University Medical Center, Rotterdam. Wound measurements using a ruler, the tracing method, the inSight® 3-dimensional (3D) device, and the ImitoWound app were performed by three investigators. The intraclass correlation coefficients (ICCs) for concurrent validity and the intra- and inter-rater reliability were analyzed. The standard error of measurement (SEm) and minimal detectable change were calculated, and Bland-Altman plots were constructed to determine the limits of agreement. RESULTS: Twenty patients with a total of 52 wounds were included. The wounds had a mean surface of 18.7 cm2. The inSight® 3D device showed an ICC of 0.987 for concurrent validity, 0.998 for intra-rater reliability, and 0.997 for inter-rater reliability. The ICCs from the ImitoWound application were 0.974, 0.978, and 0.964 for concurrent validity, intra-rater reliability, and inter-rater reliability, respectively. The SEms for intra- and inter-rater reliability were 0.95 cm2 and 1.11 cm2 for the inSight® 3D device and 3.33 cm2 and 3.51 cm2 for the ImitoWound app, respectively. CONCLUSION: Both the inSight® 3D device and the ImitoWound app demonstrated excellent concurrent validity and reliability for the surface measurements of concave wound, enabling these tools to be used reliably in clinical research and daily practice. Furthermore, it paves the way for broader application, such as telemonitoring of wound care at home.

Inter- and intraindividual variability in virtual single-tooth implant positioning.

OBJECTIVES: The purpose of this prospective study was to determine the inter- and intraindividual variability in virtual single-tooth implant positioning based on the level of expertise, specialty, total time spent, and the use of a prosthetic tooth setup. MATERIALS AND METHODS: Virtual implant planning was performed on matched pre- and post-extraction intraoral scans (IOS), and cone-beam computed tomography scans of 15 patients. Twelve individual examiners, involving six novices and experts from oral surgery and prosthodontics positioned the implants, first based on anatomical landmarks utilizing only the post-extraction, and second with the use of the pre-extraction IOS as a setup. The time for implant positioning was recorded. After 1 month, all virtual plannings were performed again. The individual implant positions were superimposed to obtain 3D deviations using a software algorithm. RESULTS: An interindividual variability with mean angular, crestal, and apical positional deviations of 3.8 ± 1.94°, 1.11 ± 0.55, and 1.54 ± 0.66 mm, respectively, was found. When assessing intraindividual variability, deviations of 3.28 ± 1.99°, 0.78 ± 0.46, and 1.12 ± 0.61 mm, respectively, were observed. Implants planned by experts exhibited statistically lower deviations compared to those planned by novices. Longer planning times resulted in lower deviations in the experts' group but not in the novices. Oral surgeons demonstrated lower crestal, but not angular and apical deviations than prosthodontists. The use of a setup only led to minor adjustments. CONCLUSIONS: Substantial inter- and intraindividual variability exists during implant positioning utilizing specialized software planning. The level of expertise and the time invested influenced the deviations of the implant position during the planning sequence.

The current role and future potential of digital diagnostic imaging in implant dentistry: A scoping review.

OBJECTIVES: Diagnostic imaging is crucial for implant dentistry. This review provides an up-to-date perspective on the application of digital diagnostic imaging in implant dentistry. METHODS: Electronic searches were conducted in PubMed focusing on the question 'when (and why) do we need diagnostic imaging in implant dentistry?' The search results were summarised to identify different applications of digital diagnostic imaging in implant dentistry. RESULTS: The most used imaging modalities in implant dentistry include intraoral periapical radiographs, panoramic views and cone beam computed tomography (CBCT). These are dependent on acquisition standardisation to optimise image quality. Particularly for CBCT, other technical parameters (i.e., tube current, tube voltage, field-of-view, voxel size) are relevant minimising the occurrence of artefacts. There is a growing interest in digital workflows, integrating diagnostic imaging and automation. Artificial intelligence (AI) has been incorporated into these workflows and is expected to play a significant role in the future of implant dentistry. Preliminary evidence supports the use of ionising-radiation-free imaging modalities (e.g., MRI and ultrasound) that can add value in terms of soft tissue visualisation. CONCLUSIONS: Digital diagnostic imaging is the sine qua non in implant dentistry. Image acquisition protocols must be tailored to the patient's needs and clinical indication, considering the trade-off between radiation exposure and needed information. growing evidence supporting the benefits of digital workflows, from planning to execution, and the future of implant dentistry will likely involve a synergy between human expertise and AI-driven intelligence. Transiting into ionising-radiation-free imaging modalities is feasible, but these must be further developed before clinical implementation.

Combining microfluidic paper-based platform and metal-organic frameworks in a single device for phenolic content assessment in fruits.

A microfluidic paper-based device (µPAD) has been combined with metal-organic frameworks (MOFs) for total phenolic compounds (TPC) quantification in fruit samples for the first time. The performance of the µPAD, based upon the vertical flow approach, was enhanced in order to determine the TPC content with high accuracy in fruit samples. The method was based on the traditional Folin-Ciocalteu Index using gallic acid or oenotannin as reference phenolic compounds. This novel design and construction of the device are in agreement with the principles of Green Chemistry avoiding wax technology (lower toxicity). The analytical parameters that affect the colorimetric method (using digital imaging of the colored zone) performance were optimized including design, sample volume, and MOF amount. Then, the analytical features of the developed method were investigated such as dynamic range (1.6-30 mg L-1), limit of detection (0.5 mg L-1), and precision (RSD < 9%). Besides, the in-field analysis is achievable with a color stability up to 6 h after the loading process of the sample and storage stability for at least 15 days without performance losses (under vacuum at - 20 °C). Furthermore, the MOF ZIF-8@paper was characterized to study its composition and the successful combination. The feasibility of the proposed method was demonstrated by determining the TPC in 5 fruit samples using oenotannin as reference solute. The accuracy was validated by comparison of the data with the results obtained with the recommended protocol proposed by the International Organisation of Vine and Wine (OIV).

RGB Achromatic Metalens Doublet for Digital Imaging.

Chromatic aberration is a major challenge faced by metalenses. Current methods to achieve broadband achromatic operation in metalenses usually suffer from limited size, numerical aperture, and working bandwidth due to the finite group delay of meta-atoms, thus restricting the range of practical applications. Multiwavelength achromatic metalenses can overcome those limitations, making it possible to realize larger numerical aperture (NA) and sizes simultaneously. However, they usually require three layers, which increases their fabrication complexity, and have only been demonstrated in small sizes, with low numerical aperture and modest efficiencies. Here, we demonstrate a 1 mm diameter red-green-blue achromatic metalens doublet with a designed NA of 0.8 and successfully apply the metalens in a digital imaging system. This work shows the potential of the doublet metasurfaces, extending their applications to digital imaging systems such as digital projectors, virtual reality glasses, high resolution microscopies, etc.

Initial Experience of 10 Imaging Vendors with the IHE SHARAZONE: a New Multivendor Peer-to-Peer Test Service for DICOM Objects.

Alignment of DICOM (Digital Imaging and Communications in Medicine) capabilities among vendors is crucial to improve interoperability in the healthcare industry and advance medical imaging 2. However, a sustainable model for sharing DICOM samples is not available. To address this issue, Integrating the Healthcare Enterprise (IHE) has introduced the IHE SHARAZONE, a continuous cross-vendor DICOM data sharing test service. IHE is a highly regarded organization known for profiling standards such as DICOM, HL7 v2 (Health Level Seven, version 2), HL7 CDA (Clinical Document Architecture), and HL7 FHIR (Fast Healthcare Interoperability Resources) into practical solutions for clinical practice. The primary goal of the IHE SHARAZONE is to provide a reliable and consistent cross-vendor DICOM data sharing system. To evaluate its effectiveness, a 5-month pilot was conducted with ten imaging vendors. The pilot concluded with a participant survey, which yielded valuable insights into the initial experience with the IHE SHARAZONE. These findings can inform future improvements and developments to this important service.

Synthesis and Application of a New Polymer with Imprinted Ions for the Preconcentration of Uranium in Natural Water Samples and Determination by Digital Imaging.

This work proposes the synthesis of a new polymer with imprinted ions (IIP) for the pre-concentration of uranium in natural waters using digital imaging as a detection technique. The polymer was synthesized using 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol (Br-PADAP) for complex formation, ethylene glycol dimethacrylate (EGDMA) as a crosslinking reagent, methacrylic acid (AMA) as functional monomer, and 2,2'-azobisisobutyronitrile as a radical initiator. The IIP was characterized by Fourier transform infrared spectroscopy and scanning electron microscopy (FTIR). Uranium determination was performed using digital imaging (ID), and some experimental conditions (sample pH, eluent concentration, and sampling flow rate) were optimized using a two-level full factorial design and Doelhert response surface methodology. Thus, using the optimized conditions, the system allowed the determination of uranium with detection and quantification limits of 2.55 and 8.51 µg L-1, respectively, and a pre-concentration factor of 8.2. All parameters were determined using a 25 mL sample volume. The precision expressed as relative deviation (RSD%) was 3.5% for a solution with a concentration of 50 µg L-1. Given this, the proposed method was used for the determination of uranium in four samples of natural waters collected in the city of Caetité, Bahia, Brazil. The concentrations obtained ranged from 35 to 75.4 µg L-1. The accuracy was evaluated by the addition/recovery test, and the values found ranged between 91 and 109%.

Radiostereometric analysis: comparison of radiation dose and precision in digital and computed radiography.

BACKGROUND: Radiostereometric Analysis (RSA) is used to measure fixation of joint prosthesis. This study compared radiation dose and image quality of a digital radiography (DR) RSA system and a computed radiography (CR) RSA system in a clinical setting. METHODS: RSA recordings of 24 hips and shoulders were analyzed. We compared two systems: (1) Arcoma T0 with ST-VI image plates and Profect CR-IR 363 reader to (2) AdoraRSA with CXDI-70C wireless DR detectors in a clinical uniplanar RSA set-up with a ± 20 degrees tube angulation and 35 cm × 43 cm detectors. Effective dose was calculated using dedicated software. Image quality was evaluated using calibration errors as calculated by the RSA software. RESULTS: The mean dose for hips was 0.14 (SD 0.04) mSv in the CR system and 0.05 (SD 0.02) mSv in the DR system. The mean dose for shoulders was 0.16 (SD 0.07) mSv in the CR system and 0.09 (SD 0.03) mSv in the DR system. Radiation dose was 64% (p < 0.001) and 43% (p = 0.03) lower in the DR system compared with the CR system for hip and shoulder RSA, respectively. Image quality was better for the DR system with 60-80% less calibration errors compared to the CR system. CONCLUSION: Owing to highly efficient detectors and added filtration at the x-ray tubes, the DR system considerably reduced radiation dose compared with the CR system without compromising image quality. Based on the findings in this study, we recommend replacing CR RSA systems with DR RSA systems. REGISTRATION: Patients were selected from clinical studies performed on the two systems and approved by the local ethics committee [20060165, M-20100112, M-20070082, M-20110224, and 20070258] and registered with ClinicalTrials.gov [NCT00408096, NCT01289834, NCT00913679, NCT02311179, and NCT00679120].

Video-based paired comparison to evaluate some cosmetic products under camera movement for dynamic performance.

OBJECTIVE: Until now, standardized evaluation of cosmetic effects was conducted mainly in still conditions such as pictures. In real life, the consumers' experience of their cosmetics' effects is dynamic and some of the benefits can be better observed under movement. In order to capture motion-related performance of cosmetics, we developed a video-based paired comparison on an online platform. METHODS: We validated this new tool through the evaluation of eyeshadow with high light reflection and colour gradation, especially visible under motion according to the observer point of view. This formula was compared with two marketed benchmarks. The three products were applied sequentially on the eyelid of eight Japanese women. Videos were taken in standardized light, speed and face position with a rotating camera around the face. The videos were uploaded on an online secured platform and eyelid 3D effect, highlight and colour gradation were evaluated through paired comparison test by 60 Japanese women from home on their PC or tablets. Those results were compared with picture-based paired comparison by the same observers. RESULTS: Video-based paired comparison provided higher discrimination of products compared to picture-based comparison. CONCLUSION: As compared to still camera acquisition, the evaluation of cosmetics based on videos is closer to real-life experience and can bring higher discrimination, especially for motion-related attributes.

OBJECTIF: Jusqu'à présent, l'évaluation standardisée des effets cosmétiques a été réalisée principalement dans des conditions immobiles telles que des photos. Dans la vie réelle, l'expérience des consommateurs des effets de leurs cosmétiques est dynamique, et certains des avantages peuvent être mieux observés en mouvement. Afin de saisir les performances des produits cosmétiques liées au mouvement, nous avons mis au point une comparaison par paires basée sur des vidéos sur une plateforme en ligne. MÉTHODES: Nous avons validé ce nouvel outil en évaluant un fard à paupières à forte réflexion lumineuse et à gradation de couleurs, particulièrement visible en mouvement selon le point de vue de l'observateur. Cette formule a été comparée à deux références commercialisées. Les trois produits ont été appliqués successivement sur la paupière de huit femmes japonaises. Les vidéos ont été prises dans des conditions de lumière, de vitesse et de position du visage normalisées, avec une caméra tournant autour du visage. Les vidéos ont été téléchargées sur une plateforme sécurisée en ligne, et l'effet 3D des paupières, l'accentuation et la gradation des couleurs ont été évalués au moyen d'un test de comparaison par paires par 60 femmes japonaises depuis leur domicile sur leur PC ou leur tablette. Ces résultats ont été mis en parallèle à une comparaison par paires sur photo par les mêmes observateurs. RÉSULTATS: La comparaison par paires sur vidéo a permis de mieux distinguer les produits par rapport à la comparaison sur photo. CONCLUSION: Par rapport à l'acquisition d'images fixes, l'évaluation des cosmétiques à partir de vidéos est plus proche de l'expérience réelle et peut permettre de mieux distinguer les produits, en particulier pour les attributs liés au mouvement.

Intra-oral scan segmentation using deep learning.

OBJECTIVE: Intra-oral scans and gypsum cast scans (OS) are widely used in orthodontics, prosthetics, implantology, and orthognathic surgery to plan patient-specific treatments, which require teeth segmentations with high accuracy and resolution. Manual teeth segmentation, the gold standard up until now, is time-consuming, tedious, and observer-dependent. This study aims to develop an automated teeth segmentation and labeling system using deep learning. MATERIAL AND METHODS: As a reference, 1750 OS were manually segmented and labeled. A deep-learning approach based on PointCNN and 3D U-net in combination with a rule-based heuristic algorithm and a combinatorial search algorithm was trained and validated on 1400 OS. Subsequently, the trained algorithm was applied to a test set consisting of 350 OS. The intersection over union (IoU), as a measure of accuracy, was calculated to quantify the degree of similarity between the annotated ground truth and the model predictions. RESULTS: The model achieved accurate teeth segmentations with a mean IoU score of 0.915. The FDI labels of the teeth were predicted with a mean accuracy of 0.894. The optical inspection showed excellent position agreements between the automatically and manually segmented teeth components. Minor flaws were mostly seen at the edges. CONCLUSION: The proposed method forms a promising foundation for time-effective and observer-independent teeth segmentation and labeling on intra-oral scans. CLINICAL SIGNIFICANCE: Deep learning may assist clinicians in virtual treatment planning in orthodontics, prosthetics, implantology, and orthognathic surgery. The impact of using such models in clinical practice should be explored.