An evaluation of the diagnostic performance of the triphasic bone scintigraphy in patients suspected of aseptic total knee arthroplasty loosening.

Background: Total Knee Arthroplasty (TKA) is a widely conducted and successful orthopedic procedure. However, aseptic loosening, a common cause of TKA failure, necessitates revision surgery. Diagnostic accuracy of triphasic bone scintigraphy, a common imaging modality for aseptic loosening detection, remains controversial. This study investigated the diagnostic accuracy of bone scintigraphy when separately evaluated by a nuclear physicist and an orthopedic surgeon, and the interrater reliability between the two. Methods: Patients undergoing knee revision surgery due to suspected aseptic loosening at three medical centers from 2006 to 2023 were included. Relevant demographic, clinical, and procedural data were extracted from the records. The bone scintigraphy results as noted by the nuclear physicist and orthopedic surgeon were used as index test and intraoperative findings of loosening were used as reference tests. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated, and kappa's agreement was assessed. Results: Out of 611 revision TKAs, 59 cases were analyzed. The nuclear physicist's evaluation of bone scintigraphy had a sensitivity of 73 %, specificity of 0 %, positive predictive value of 93 %, negative predictive value of 0 %, and diagnostic accuracy of 69 %. The orthopedic surgeon's evaluation showed higher sensitivity, specificity, positive and negative predictive values, and an accuracy of 84 %. Agreement levels were moderate (kappa = 0.46) between the nuclear physicist's and orthopedic surgeons evaluation. Interpretation: The diagnostic accuracy of bone scintigraphy for aseptic loosening is 84 % when evaluated by the orthopedic surgeon compared to 69 % for the nuclear physicist's evaluation. Kappa's agreement between the two was moderate.

Assessing the Predictive Accuracy of the aMAP Risk Score for Hepatocellular Carcinoma (HCC): Diagnostic Test Accuracy and Meta-analysis.

Purpose: We aimed to perform a meta-analysis with the intention of evaluating the reliability and test accuracy of the aMAP risk score in the identification of HCC. Methods: A systematic search was performed in PubMed, Scopus, Cochrane, Embase, and Web of Science databases from inception to September 2023, to identify studies measuring the aMAP score in patients for the purpose of predicting the occurrence or recurrence of HCC. The meta-analysis was performed using the meta package in R version 4.1.0. The diagnostic accuracy meta-analysis was conducted using Meta-DiSc software. Results: Thirty-five studies 102,959 participants were included in the review. The aMAP score was significantly higher in the HCC group than in the non-HCC group, with a mean difference of 6.15. When the aMAP score is at 50, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.961 (95% CI 0.936, 0.976), 0.344 (95% CI 0.227, 0.483), 0.114 (95% CI 0.087, 0.15), and 1.464 (95% CI 1.22, 1.756), respectively. At a cutoff value of 60, the pooled sensitivity, specificity, negative likelihood ratio, and positive likelihood ratio with 95% CI was 0.594 (95% CI 0.492, 0.689), 0.816 (95% CI 0.714, 0.888), 0.497 (95% CI 0.418, 0.591), and 3.235 (95% CI 2.284, 4.582), respectively. Conclusion: The aMAP score is a reliable, accurate, and easy-to-use tool for predicting HCC patients of all stages, including early-stage HCC. Therefore, the aMAP score can be a valuable tool for surveillance of HCC patients and can help to improve early detection and reduce mortality.

Exploratory investigation of virtual lesions in gastrointestinal endoscopy using a novel phase-shift method for three-dimensional shape measurement.

Accurate measurement of the size of lesions or distances between any two points during endoscopic examination of the gastrointestinal tract is difficult owing to the fisheye lens used in endoscopy. To overcome this issue, we developed a phase-shift method to measure three-dimensional (3D) data on a curved surface, which we present herein. Our system allows the creation of 3D shapes on a curved surface by the phase-shift method using a stripe pattern projected from a small projecting device to an object. For evaluation, 88 measurement points were inserted in porcine stomach tissue, attached to a half-pipe jig, with an inner radius of 21 mm. The accuracy and precision of the measurement data for our shape measurement system were compared with the data obtained using an Olympus STM6 measurement microscope. The accuracy of the path length of a simulated protruded lesion was evaluated using a plaster model of the curved stomach and graph paper. The difference in height measures between the measurement microscope and measurement system data was 0.24 mm for the 88 measurement points on the curved surface of the porcine stomach. The error in the path length measurement for a lesion on an underlying curved surface was <1% for a 10-mm lesion. The software was developed for the automated calculation of the major and minor diameters of each lesion. The accuracy of our measurement system could improve the accuracy of determining the size of lesions, whether protruded or depressed, regardless of the curvature of the underlying surface.

Accuracy of ChatGPT responses on tracheotomy for patient education.

OBJECTIVE: To investigate the accuracy of information provided by ChatGPT-4o to patients about tracheotomy. METHODS: Twenty common questions of patients about tracheotomy were presented to ChatGPT-4o twice (7-day intervals). The accuracy, clarity, relevance, completeness, referencing, and usefulness of responses were assessed by a board-certified otolaryngologist and a board-certified intensive care unit practitioner with the Quality Analysis of Medical Artificial Intelligence (QAMAI) tool. The interrater reliability and the stability of the ChatGPT-4o responses were evaluated with intraclass correlation coefficient (ICC) and Pearson correlation analysis. RESULTS: The total scores of QAMAI were 22.85 ± 4.75 for the intensive care practitioner and 21.45 ± 3.95 for the otolaryngologist, which consists of moderate-to-high accuracy. The otolaryngologist and the ICU practitioner reported high ICC (0.807; 95%CI: 0.655-0.911). The highest QAMAI scores have been found for clarity and completeness of explanations. The QAMAI scores for the accuracy of the information and the referencing were the lowest. The information related to the post-laryngectomy tracheostomy remains incomplete or erroneous. ChatGPT-4o did not provide references for their responses. The stability analysis reported high stability in regenerated questions. CONCLUSION: The accuracy of ChatGPT-4o is moderate-to-high in providing information related to the tracheotomy. However, patients using ChatGPT-4o need to be cautious about the information related to tracheotomy care, steps, and the differences between temporary and permanent tracheotomies.

Is AI chatbot recommendation convincing customer? An analytical response based on the elaboration likelihood model.

The integration of artificial intelligence (AI) technology in e-commerce has currently stimulated scholarly attention, however studies on AI and e-commerce generally relatively few. The current study aims to evaluate how artificial intelligence (AI) chatbots persuade users to consider chatbot recommendations in a web-based buying situation. Employing the theory of elaboration likelihood, the current study presents an analytical framework for identifying factors and internal mechanisms of consumers' readiness to adopt AI chatbot recommendations. The authors evaluated the model employing questionnaire responses from 411 Chinese AI chatbot consumers. The findings of present study indicated that chatbot recommendation reliability and accuracy is positively related to AI technology trust and have negative effect on perceived self-threat. In addition, AI technology trust is positively related to intention to adopt chatbot decision whereas perceived self-threat negatively related to intention to adopt chatbot decision. The perceived dialogue strengthens the significant relationship between AI-tech trust and intention to adopt chatbot decision and weakens the negative relationship between perceived self-threat and intention to adopt AI chatbot decisions.

Systematic review and meta-analysis of the diagnostic accuracy of inflammatory markers for infected diabetic foot ulcer.

BACKGROUND: The aim was to evaluate the diagnostic value of ESR, CPR, PCT, and WBC in patients with infected diabetic foot ulcer (DFU). METHODS: The MEDLINE, Embase, BIOSIS, Cochrane databases, and Web of Knowledge databases were searched, without language restriction, to July 2023. Original studies were selected that reported the performance of ESR, CPR, PCT, and WBC in diagnosing infected DFU. To assess the diagnostic value of biomarkers for infected DFU, pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic curve (ROC-AUC) were calculated. RESULTS: Ten studies with 765 patients were identified in our meta-analysis. The pooled sensitivity and specificity of ESR was 0.82 (95 % CI: 0.68-0.91) and 0.83 (95 % CI: 0.69-0.91) respectively. The pooled sensitivity and specificity of CRP was 0.81 (95 % CI: 0.65-0.91) and 0.91 (95 % CI: 0.79-0.96) respectively. The pooled sensitivity and specificity of PCT was 0.76 (95 % CI: 0.65-0.85) and 0.89 (95 % CI: 0.78-0.95) respectively. The pooled sensitivity and specificity of WBC was 0.75 (95 % CI: 0.64-0.83) and 0.79 (95 % CI: 0.67-0.88) respectively. CRP showed the best diagnostic accuracy at distinguishing infected DFU from noninfected DFU with an AUC of 0.93, followed by PCT (AUC of 0.89), ESR (AUC of 0.89), and WBC (AUC of 0.84). CONCLUSION: CPR levels had high efficiency in distinguishing infected DFU from noninfected DFU, followed by PCT, ESR and WBC. All of these biomarkers could be helpful for early diagnosis of infected DFU. New biomarkers for improving medical decision in diagnosis of infected DFU are highly desirable.

Clinical evaluation of a multiplex PCR-based test for joint infection: a prospective diagnostic accuracy study of forty-nine patients.

PURPOSE: The purpose of this study was to evaluate the diagnostic accuracy (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)) of the PCR-based BioFire® Joint Infection Panel (BJI Panel) against microbiological culture growth for patients suspected of having a native or prosthetic joint infection. METHODS: Synovial fluid and tissue biopsies were prospectively collected from patients from June 2022 to June 2023. The results of the BJI Panel were compared with those of culture growth. RESULTS: 51 samples were included. Including all pathogens, the sensitivity was 69%, the specificity 89%, the PPV 73% and the NPV 86%. Including only pathogens in the BJI Panel, the sensitivity was 100%, the specificity 90%, the PPV 73% and the NPV 100%. CONCLUSION: The BJI Panel has a high accuracy for detecting the pathogens in its panel, but the absence of important common pathogens from the panel reduces its sensitivity and NPV. With a short turnaround time and precise pathogen detection, the BJI Panel has the potential to add value as a complementary diagnostic method.

Gastric-type extremely well-differentiated adenocarcinoma of the stomach: A rare tumor with diagnostic difficulties and high inter-observer variation in endoscopic pinch biopsies.

Extremely well-differentiated gastric-type adenocarcinoma (EWDGA) is a rare type of gastric cancer composed of deceptively bland-looking malignant cells resembling normal foveolar or pyloric epithelium. The histological features of this tumor have not been recognized by many pathologists, and inter-observer variation studies are lacking. Here, we report seven EWDGAs and inter-observer variation of six preoperative biopsies was evaluated by 11 pathologists in a single institute. Based on the pathological diagnosis of the endoscopic biopsy slides, the average rate of definite malignancy diagnosis was 15.2 %, and the overall diagnostic concordance rate was 34.9 % among 11 pathologists. Microscopically, the surface epithelium was preserved and only a few atypical tumor glands were scattered in most endoscopic biopsies. Structural atypia was minimal, and the tumor glands were barely distinguishable from normal glands. Although nuclear atypia was minimal, enlarged nuclei, relatively large glands with irregular shapes, and abundant cytoplasmic mucin were observed in gastric pinch biopsies. In preoperative biopsies, no cases showed p53 overexpression, and Ki-67 labeling index ranged from 3 % to 35 % and was higher compared to non-neoplastic glands in 3 cases. After gastrectomy, four (57.1 %) patients had advanced gastric cancer and three (42.9 %) had lymph node metastasis. Genomic profiling of the four patients revealed mutations of TP53, BRAF, KRAS, STK11, and MDM2/CCND1 amplification. Immunohistochemistry for p53 was not helpful while Ki-67 may be helpful when staining pattern is distinct from the non-neoplastic mucosa. In conclusion, it is challenging to diagnose EWDGA using biopsy specimens. Recognizing and addressing this rare entity will increase diagnostic accuracy to ensure the early diagnosis of cancer.

Zirconia crowns manufactured using digital light processing: Effects of printing angle and layer thickness on the accuracy.

OBJECTIVES: This study investigated the effects of build angle and layer thickness on the trueness and precision of zirconia crowns manufactured using digital light processing (DLP) technology. MATERIALS AND METHODS: Single crowns were fabricated from zirconia using DLP technology. The crowns were manufactured with three different representative build angles (0°, 45°, and 90°) and two different layer thicknesses (30 µm and 50 µm). After printing, the specimens were non-contact-scanned, and their accuracy was assessed using a 3D analysis software. Root mean square (RMS) values were used to determine trueness and precision. Color maps were generated to detect deviations within the specimens. Statistical analyses were conducted using two-way ANOVA. RESULTS: Build angle and layer thickness significantly affected trueness and precision (p < 0.05). At a 30-µm layer thickness, the crowns printed at angles of 0° (32.2 ± 3.2 µm) and 45° (33.9 ± 2.4 µm) demonstrated the best marginal trueness compared to those in other groups (p < 0.05). Notably, those printed at an angle of 90° exhibited the best intaglio surface trueness (37.4 ± 4.0 µm). At a 50-µm layer thickness, the crowns printed at an angle of 90° exhibited the lowest accuracy concerning marginal and intaglio surface aspects (27.7 ± 8.2 µm). CONCLUSIONS: Both the build angle and layer thickness significantly affected the dimensional accuracy of DLP-printed zirconia crowns, with the 30-µm layer thickness offering superior trueness. Optimal results were achieved using build angles of 0° and 45° in conjunction with thinner layers, minimizing marginal defects. CLINICAL SIGNIFICANCE: All zirconia crowns produced at different build angles and layer thicknesses satisfied clinical requirements. Specific combinations of these factors realized the fabrication of single crowns that possessed the highest accuracy.

Comparison of etonogestrel bioanalytical assay results in plasma and serum within and across laboratories.

OBJECTIVES: To compare performance characteristics of etonogestrel bioanalytical assays across laboratories. STUDY DESIGN: We conducted a blinded, six laboratory study: five academic laboratories and one contracted commercial laboratory (reference). Etonogestrel was quantitated at each laboratory in both prepared serum and/or plasma samples of six known etonogestrel concentrations, and in 60 clinical samples from participants using etonogestrel-containing contraceptive methods. Per regulatory guidance, laboratory accuracy (percent bias) and precision (coefficient of variation; CV) were defined as ±15% of the nominal prepared concentration. We compared inter- and intra-laboratory agreement using a Kendall's Tau-B and Passing-Bablok regression. RESULTS: For prepared samples, six laboratories analyzed serum and three laboratories analyzed plasma. All etonogestrel results were within ±15% for accuracy across all concentrations at four labs, including the reference laboratory. All labs demonstrated high precision, with only one occurrence of CV >15%. We found a positive association between prepared plasma and serum etonogestrel results (Kendall's Tau-B 0.80-0.88). For clinical samples, five laboratories analyzed serum and three laboratories analyzed plasma. Compared to the reference laboratory, inter-laboratory serum etonogestrel concentrations were positively correlated (Kendall's Tau-B 0.76-0.95). Proportional bias was observed, meaning individual lab etonogestrel results were consistently higher (slope estimates 0.78-0.95) or lower (slope estimates 1.05-1.10) than the reference laboratory. In clinical samples, intra-laboratory results were well associated between plasma and serum (Kendall's Tau-B 0.92-0.96). CONCLUSION: There was good intra-laboratory agreement, irrespective of sample matrix; however, there was inter-laboratory variability in etonogestrel results. Differences between laboratory results should be considered when comparing etonogestrel pharmacokinetics across studies.

Ultrasonography-Guided Dental Implant Surgery: A Feasibility Study.

OBJECTIVE: To evaluate the feasibility of ultrasound-image-based computer-assisted implant planning and placement. MATERIALS AND METHODS: Intraoral scans, cone-beam computerized tomography (CBCT), and ultrasound (US) scans with a custom positioning device were acquired in nine patients. Prosthetic-driven surgical guides were planned and fabricated based on ultrasound images and intraoral scans. Implants were then placed. Postoperative implant position was obtained intra-surgically by intraoral scan. Aside from the ultrasound-based plan, conventional implant planning was performed by the same operator on a pre-surgical CBCT for comparison. Linear deviations between ultrasound and CBCT-planned implant positions were measured and compared with the intra-surgical implant position, and the position deviations between two consecutive plannings were performed on the same CBCT by the same operator. The linear deviation between the 3D scan surface of the edentulous region and the ultrasonographic soft tissue profile segmentation was also assessed with reverse-engineering software. Means, standard deviations, and root mean square differences (RMSD) were calculated for every variable. RESULTS: All the ultrasound-planned implants were successfully placed, and no complications were recorded. The mean deviations in angles, shoulders, and apexes were 5.27 ± 1.75° (RMSD: 5.53°), 0.92 ± 0.26 mm (RMSD: 0.95 mm), and 1.41 ± 0.61 mm (RMSD: 1.53 mm), respectively, between the US and CBCT-planned implants; 2.63 ± 0.43° (RMSD: 2.66°), 1.16 ± 0.30 mm (RMSD: 1.19 mm), and 1.26 ± 0.27 mm (RMSD: 1.28 mm) between the planned implant and intra-surgically recorded positions; and 2.90 ± 1.36° (RMSD: 3.18°), 0.65 ± 0.27 mm (RMSD: 0.70 mm), and 0.99 ± 0.37 mm (RMSD: 1.05 mm) between two consecutive CBCTs planning performed by the same operator. The mean deviation between the 3D surfaces of model scans and ultrasound-derived soft tissue profile in the edentulous area was 0.19 ± 0.08 mm. CONCLUSIONS: Ultrasound-guided implant surgery represents a feasible non-ionizing alternative to conventional static guided implant surgical protocols for implant placement in sites with favorable characteristics.

3-axis computer numerical control machine positioning error dataset for thermal error compensation.

This article reports on a comprehensive dataset detailing positioning errors in a 3-axis milling center machine (MCM) with computer numerical control (CNC) specifically curated for thermal error compensation. The data, which includes separate datasets for the X, Y, and Z axes, was collected through systematic measurements using an interferometric laser (IL) system under monitored thermal conditions. Each axis's acquisition was recorded with a resolution to capture dynamic variations influenced by thermal fluctuations. Temperature measurements were obtained using resistance temperature detectors (RTD) installed in the bearing housings of each axis for monitoring of thermal conditions throughout the data collection process in each axis. The dataset comprises raw positional and error data for each axis alongside metadata describing parameters such as bearing temperature, heating cycle, and machine operating conditions. This dataset can potentially be a valuable resource for researchers, enabling them to develop and validate real-time thermal error compensation algorithms, thereby enhancing CNC machining precision for each axis independently and collectively. Furthermore, the dataset's structured format facilitates comparative studies across different machine configurations and operational contexts, contributing to advancements in manufacturing technology and improvements in process parameter design and optimization.

rRNA operon improves species-level classification of bacteria and microbial community analysis compared to 16S rRNA.

Precise identification of species is fundamental in microbial genomics and is crucial for understanding the microbial communities. While the 16S rRNA gene, particularly its V3-V4 regions, has been extensively employed for microbial identification, however has limitations in achieving species-level resolution. Advancements in long-read sequencing technologies have highlighted the rRNA operon as a more accurate marker for microbial classification and analysis than the 16S rRNA gene. This study aims to compare the accuracy of species classification and microbial community analysis using the rRNA operon versus the 16S rRNA gene. We evaluated the species classification accuracy of the rRNA operon,16S rRNA gene, and 16S rRNA V3-V4 regions using a BLAST-based method and a k-mer matching-based method with public data available from NCBI. We further performed simulations to model microbial community analysis. We accessed the performance using each marker in community composition estimation and differential abundance analysis. Our findings demonstrate that the rRNA operon offers an advantage over the 16S rRNA gene and its V3-V4 regions for species-level classification within the genus. When applied to microbial community analysis, the rRNA operon enables a more accurate determination of composition. Using the rRNA operon yielded more reliable results in differential abundance analysis as well. IMPORTANCE: We quantitatively demonstrated that the rRNA operon outperformed the 16S rRNA and its V3-V4 regions in accuracy for both individual species identification and species-level microbial community analysis. Our findings can provide guidelines for selecting appropriate markers in the field of microbial research.

Assessment of accuracy of two pulse oximeters in infants with cyanotic and acyanotic congenital heart diseases.

BACKGROUND: Peripherally measured oxygen saturation (SpO2) may often differ from arterial oxygen saturation (SaO2), measured by co-oximetry, especially within the lower range of oxygen saturations. This can potentially impact clinical decisions and therapy in children with congenital heart disease, as critical hypoxemia might remain unnoticed. AIMS: Our aim was to investigate the accuracy of two different pulse oximeters compared to SaO2 in infants with congenital heart diseases. METHODS: Simultaneous recordings of SpO2, measured by two different pulse oximeters (Philips IntelliVue X3 Monitor and Nellcor™ OxiMax™), were compared to SaO2 obtained by arterial blood gas analysis. RESULTS: A total of 153 measurements were performed in 44 infants with arterial oxygen saturation between 70 and 100%. We divided the measurements into 3 subgroups: group 1-SaO2 70.0%-85.0%, group 2-SaO2 85.1%-94.0%, group 3-SaO2 >94.1%. For Philipps, the median bias was 5.3 (IQR: 2.6-8.7) %, 2.3 (IQR: 0.9-6.0) % and 1.1 (IQR: -0.8-2.4) % in group 1, 2 and 3, respectively. For OxiMax™, the median bias was 2.7 (IQR: 0.5-5.1) %, 0.2 (IQR: -0.9-2.6) % and -0.5 (IQR: -1.3-0.6) % in group 1, 2 and 3, respectively. Regarding the accuracy of these oximeters, as evaluated with the Accuracy root mean squared index (Arms), it was 9.8 versus 4.5% in group 1, 4.5 versus 2.9% in group 2 and 2.4 versus 1.9% in group 3 for Philipps and OxiMax™, respectively. CONCLUSIONS: In lower range saturations between 70% and 85% the accuracy of both pulse oximeters exceeded the threshold of ≤3% recommended by the Food and Drug Administration (FDA). Therefore, peripheral pulse oximetry within the lower range of oxygen saturations should be interpreted with caution in infants with congenital heart diseases, taking into consideration its limitations. Direct co-oximetry should be the preferred method to support clinical decisions in children with cyanotic congenital heart diseases.

Impact of landmark crater creation on improving accuracy of pedicle screw insertion in robot-assisted scoliosis surgery.

PURPOSE: This study evaluated the impact of the Landmark Crater (LC) method on pedicle perforation rates in robot-guided surgery for pediatric scoliosis for each pedicle diameter. METHODS: Seventy-six scoliosis patients underwent robot-assisted posterior spinal fusion. The cohort consisted of 19 male and 57 female patients, with a mean ± standard deviation age of 17.5 ± 7.7 years and a preoperative Cobb angle of 57.0 ± 18.5°. The LC method is a method in which craters that serves as a landmark are created in advance at the planned PS insertion site of all pedicles within the intraoperative CT imaging area. The patients were divided into the LC group, in which PS insertion was performed using the LC method, and the control group using the conventional PS insertion method. Overall and pedicle perforation rates for each pedicle outer diameter were compared between the groups by Fisher's exact test. RESULTS: The LC group exhibited a significantly lower pedicle major perforation rate than did the control group (2.7% vs. 6.2%, P = 0.001). The perforation rates in pedicles with a pedicle outer diameter > 6 mm, 4-6 mm, 2-4 mm, and < 2 mm were 0.61%, 1.6%, 5.1%, and 21%, in the LC group and 0.75%, 4.1%, 12%, and 50% in the control group, respectively. CONCLUSION: In robot-assisted surgery for pediatric scoliosis, the LC method enabled significantly lower pedicle perforation rates over the conventional method. Both the LC and conventional methods exhibited higher perforation rates for smaller pedicle diameters.

Is bracket bonding with guided bonding devices accurate enough for crowded dentition?

BACKGROUND: This research aimed to study whether bracket bonding using guided bonding devices (GBDs) is accurate enough for crowded dentitions in vitro. METHODS: Fifteen three-dimensionally (3D) printed resin model sets were included and divided into three groups: mild, moderate, and severe crowding. The resin models were scanned and virtually bonded with brackets. Corresponding GBDs were generated and 3D printed. Subsequently, the brackets were bonded to the resin models on a dental mannequin using the GBDs. The models with bonded brackets were scanned, and comparisons were made between the positions of the actually bonded and the planned ones to evaluate possible deviations. RESULTS: There was no immediate bonding failure in any group. The bonding duration tended to increase with crowding severity (P > 0.05). Almost all linear and angular deviations in all groups were below 0.5 mm and 2°, respectively, and no statistically significant difference was found among the different crowding degrees (P > 0.05). In all groups, the brackets tended to deviate lingually and had buccal crown torque. Brackets in the groups with mild and severe crowding showed a tendency for mesiobuccal rotation. CONCLUSION: GBDs provide high bracket bonding accuracy for dentitions with different crowding degrees and, thus, could hopefully be applied to uncrowded and crowded dentitions alike.

Diagnostic Accuracy of USG and MRI for the Detection of Rotator Cuff Injury.

INTRODUCTION: Rotator cuff disease frequently causes shoulder pain and is diagnosed using various radiological methods alongside history and physical examination. Arthrography has traditionally been employed for this purpose, but newer non-invasive techniques such as ultrasonography (USG) and magnetic resonance imaging (MRI) are increasingly used. However, no single method is universally agreed upon as the best diagnostic tool, each having its own limitations. OBJECTIVES: To evaluate how effectively ultrasound and MRI can diagnose rotator cuff tears. MATERIALS AND METHODS: Seventy patients suspected of having a rotator cuff tear underwent investigations at the Radiology Department of Krishna Vishwa Vidyapeeth (Deemed to be University), Karad. USG and MRI examinations were done on the same day, along with a detailed history. USG was conducted using a GE LOGIQ P9 machine with a high-frequency 3-12 MHz transducer. MRI was conducted using a 1.5T Siemens Magnetom Avanto scanner. RESULTS: Pain and stiffness are the most common complaints in rotator cuff tears. The predisposing factors include male predominance, increasing age, dominant hand use, and trauma history. The supraspinatus tendon is the most frequently injured, with partial tears, especially articular surface tears, being more common than full-thickness tears. Clinical examinations, USG, and MRI are valuable in diagnosing rotator cuff tears. CONCLUSION: Our findings indicate that USG may not be as reliable in detecting rotator cuff tears as once believed. A positive ultrasound result is more trustworthy than a negative one. In contrast, MRI demonstrates greater sensitivity and overall diagnostic accuracy compared to both ultrasonography and clinical assessment for detecting rotator cuff tears.

Accuracy of implant abutment level digital impressions using stereophotogrammetry in edentulous jaws: an in vitro pilot study.

BACKGROUND: In edentulous jaws, factors such as the number of implants, cross-arch distribution, and the angle among implants may affect the accuracy of the implant impression. This study explored factors influencing the accuracy of implant abutment-level digital impressions using stereophotogrammetry in edentulous jaws. METHODS: Two standard all-on-4 and all-on-6 models of edentulous jaws were constructed in vitro. In the stereophotogrammetry group (PG), the implant digital impression was made using stereophotogrammetry and saved as an STL file. In the conventional group (CNV), the impression was made using the open-tray splint impression technique. An electronic and optical 3D measuring instrument was used to scan the standard model and the conventional plaster model to obtain STL files. Using 3D data processing software (GOM Inspect Pro, Zeiss), the distance and angle between the abutments in the CNV impression and the PG impression were measured and compared with the data from the standard model. RESULTS: The distance deviation in the PG and the CNV was 145 ± 196 µm and 96 ± 150 µm, respectively, with a significant difference (P < 0.001). The angle deviation in the PG and the CNV was 0.82 ± 0.88° and 0.74 ± 0.62°, respectively, with no significant difference (P = 0.267). In the PG, the distance deviation was negatively correlated with the distance between implants (r = -0.145, P = 0.028) and positively correlated with the angle of implants (r = 0.205, P = 0.002). The angle deviation was negatively correlated with the distance between implants (r = -0.198, P = 0.003) and positively correlated with the angle of implants (r = 0.172, P = 0.009). In the CNV, the effect of inter-implant distance on impression accuracy was also shown by Spearman correlation analysis: r = 0.347 (P < 0.001) for distance deviation and r = -0.012 (P = 0.859) for angle deviation. The effect of inter-implant angulation on impression accuracy deviation was r = -0.026 (P = 0.698) for distance deviation and r = 0.056 (P = 0.399) for angle deviation. CONCLUSIONS: The CNV method is closer to the real value of the original model. The distance between implants and the distribution angle had a weak correlation with the accuracy of digital impressions but no significant correlation with the accuracy of traditional impressions.

People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation.

The rise of generative AI tools has sparked debates about the labeling of AI-generated content. Yet, the impact of such labels remains uncertain. In two preregistered online experiments among US and UK participants (N = 4,976), we show that while participants did not equate "AI-generated" with "False," labeling headlines as AI-generated lowered their perceived accuracy and participants' willingness to share them, regardless of whether the headlines were true or false, and created by humans or AI. The impact of labeling headlines as AI-generated was three times smaller than labeling them as false. This AI aversion is due to expectations that headlines labeled as AI-generated have been entirely written by AI with no human supervision. These findings suggest that the labeling of AI-generated content should be approached cautiously to avoid unintended negative effects on harmless or even beneficial AI-generated content and that effective deployment of labels requires transparency regarding their meaning.

The Role of Artificial Intelligence and Machine Learning in Cardiovascular Imaging and Diagnosis.

Cardiovascular diseases remain the leading cause of global mortality, underscoring the critical need for accurate and timely diagnosis. This narrative review examines the current applications and future potential of artificial intelligence (AI) and machine learning (ML) in cardiovascular imaging. We discuss the integration of these technologies across various imaging modalities, including echocardiography, computed tomography, magnetic resonance imaging, and nuclear imaging techniques. The review explores AI-assisted diagnosis in key areas such as coronary artery disease detection, valve disorders assessment, cardiomyopathy classification, arrhythmia detection, and prediction of cardiovascular events. AI demonstrates promise in improving diagnostic accuracy, efficiency, and personalized care. However, significant challenges persist, including data quality standardization, model interpretability, regulatory considerations, and clinical workflow integration. We also address the limitations of current AI applications and the ethical implications of their implementation in clinical practice. Future directions point towards advanced AI architectures, multimodal imaging integration, and applications in precision medicine and population health management. The review emphasizes the need for ongoing collaboration between clinicians, data scientists, and policymakers to realize the full potential of AI in cardiovascular imaging while ensuring ethical and equitable implementation. As the field continues to evolve, addressing these challenges will be crucial for the successful integration of AI technologies into cardiovascular care, potentially revolutionizing diagnostic capabilities and improving patient outcomes.