To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

To address the problem of data silos in dental specialties caused by equipment heterogeneity, this study developed an Intelligent Internet of Things (IoT)-enabled dental chair platform (hereinafter referred to as the intelligent platform) based on the concept of medical-engineering integration. The platform adopts a three-tier chair-domain interconnection architecture: the bottom tier integrates multi-source sensors and standardized interfaces for automated data acquisition and linkage with hospital information systems; the middle tier provides clinic-level management and remote teaching collaboration; and the top tier employs a blockchain-based secure cloud database for resource allocation and data management. Clinical validation at The Affiliated Stomatological Hospital of Nanjing Medical University demonstrated that, compared with a control group from the same period in 2023, the trial group achieved a 38.0% increase in average daily patient visits (80.6±6.8 vs. 58.4±5.2, t=15.16, P<0.001), a 24.6% reduction in average treatment time [(36.1±6.3) min vs. (47.9±8.5) min, t=7.72, P<0.001], a 39.2% reduction in waiting time [23.3 (16.5, 30.1) min vs. 38.3 (28.3, 48.3) min, U=32.00, P<0.001], a 30.4% reduction in equipment idle rate [8.7% (5.1%, 12.3%) vs. 12.5% (7.4%, 17.6%), U=251.00, P=0.003], and an increase in patient satisfaction from 88.2% (1 519/1 723) to 94.3% (2 186/2 318) ( t=7.26, P<0.001). User research confirmed that the functions most favored by clinicians and patients were "dental chair parameter updating and clinical data integration" [74.7% (80/107)] and "chairside display of diagnostic images" [76.8% (119/155)], respectively. Looking forward, the intelligent platform has the potential to integrate artificial intelligence-assisted diagnosis and 5G-enabled multicenter collaboration to further expand its clinical applications and accelerate the digital transformation of dental healthcare.

Objective To investigate the clinical application of 3D printed bolus with specific density in breast cancer radiotherapy,and to evaluate its effects on dose distribution and positioning.Methods Forty post-mastectomy patients undergoing intensity-modulated radiotherapy were randomly enrolled for 3D printed bolus(n=20)and conventional bolus(n=20),and all patients were fixed in the supine position using styrofoam.Conventional positioning was performed based on in-room lasers and body markers,with daily Catalyst HD optical surface monitoring combined with weekly CBCT verification.The absolute dose,patients'skin surface dose,surgical incision,planned field,target area doses(VCTV50Gy,VPTV50Gy)and organs-at-risk doses in patients with different boluses were recorded,and the conformity index and homogeneity index were calculated,and the setup errors using CBCT and Catalyst HD were also analyzed.Results The difference in absolute dose between different boluses was trivial,but the skin surface dose with 3D printed bolus was significantly higher than with conventional bolus[(54.83±0.44)Gyvs(54.43±0.51)Gy,P<0.05].Patients with 3D printed boluses had a higher conformity index than with conventional boluses(0.69±0.04 vs 0.65±0.02).For different boluses,there was no significant difference in VCTV50 Gy,while the VPTV50 Gy and organs-at-risk doses were lower in those with 3D printed bolus than conventional boluses(P<0.05),with heart Vmean of 9.68%±3.24%vs11.43%±3.60%.In patients with 3D printed boluses,both planned field arrangement and surgical incision affected the target doses,and the doses of the target area without an internal breast wrap was greater than those with internal breast wrap(P<0.05).When the field was not wrapped around the internal breast,the surgical incisions only affected VPTV50 Gy,and the VPTV50 Gy was greater with the transverse fusiform incision than with the oblique vertical incision(P<0.05),which were 95.58%±0.51%vs95.44%±0.71%.The optical monitoring accuracies with different boluses differed only in the left-right direction(P<0.05),with(0.08±0.57)cm and(-0.15±0.46)cm for 3D printed and conventional boluses.Conclusion Compared with conventional bolus,3D printed bolus can improve dose distribution and optical monitoring accuracy.The surgical incision and planned field arrangement under 3D-printed bolus would exert effects on target doses.

Objective:To explore the influence of the contours of different parts of the human body on the setup errors of Catalyst HD optical surface imaging (OSI) system-guided radiotherapy.Methods:Using the 3D printing technology, arc- and oval arc-shaped phantoms with base angles of 5°-45° (step length: 5°) were designed to simulate the contours of different body parts of patients. A Catalyst HD system was employed for monitoring, during which the gains and integration time of the system were adjusted. The treatment couches were manually moved (range: -5 mm to 5 mm, with a step length of 2 mm). The ratios of transverse to longitudinal dimensions of all phantoms were recorded. The recorded items also included couch value errors in the anterior-posterior (AP), inferior-superior (SI), and left-right (LR) directions for transversely and longitudinally placed phantoms, as well as the setup errors monitored using the Catalyst HD system. Then, this study presented an analysis of the correlation between phantoms for different body contours and the gains and integration time of the Catalyst HD system. The purpose was to compare the setup errors under the two different placement conditions of phantoms and to analyze the correlation between the monitored values of the Catalyst HD system and couch values.Results:There was a significant linear negative correlation between the gain and the logarithm of integration time required for monitoring using the Catalyst HD system, with a slope of -0.001. There was a certain functional relationship between the intercept and the ratio of the transverse to longitudinal dimensions of the phantoms. Under the same gain, the integration time decreased with an increase in the base angles of phantoms. The Catalyst HD system showed different monitoring accuracy under different placement conditions of the phantoms ( Z = -8.59 to -0.02, P < 0.05), with the monitoring accuracy in the LR and AP directions higher in the transverse position. The correlation between the monitored values of the Catalyst HD system and the actual couch values increased in the LR and SI directions with an increase in the base angle of the phantoms, showing a strong correlation in the case of base angles of ≥ 25°. Furthermore, the correlation was always significant in the AP direction ( R > 0.9). Conclusions:When the best surface images are obtained using the Catalyst HD system, the gains and integration time of the system are correlated with body surface contours. The Catalyst HD system shows high monitoring accuracy in the AP direction. This system shows high accuracy in all directions when the ratios of transverse to longitudinal dimensions are ≤ 2 or the base angles ≥ 25°.

Objective:To evaluate the effectiveness of the information management system on the clinical application of special-grade antimicrobial.Methods:Using the established knowledge database, a computer program was designed and developed, which was embedded in the electronic medical record to intervene the clinical use of the special-grade antimicrobial since 2015. The basic information of all discharged patients from the Second Affiliated Hospital of Zhejiang University School of Medicine from January 2013 to December 2020 were extracted from the HIS system, including the medical orders for antibiotics and the drug storehouse dispensing data.The trend analysis was carried out on the changes of the use rates and antibiotic use density (AUD) of the special-grade antimicrobials in the whole hospital and intensive care units (ICU). The data were processed and analyzed using SPSS 24.0.Results:From 2013 to 2015, except for meropenem and amphotericin B, the usage rate of all special-grade antimicrobials in the whole hospital showed an upward trend ( P<0.05). The proportion of special-grade antimicrobials used in the hospital increased year by year ( χ2=7 804.081, P<0.01). The total usage rate of special-grade antimicrobials in ICU showed an upward trend year by year ( χ2=67.028, P<0.01). Since the implementation of the special-grade antimicrobial information management system in 2015, the total use rate of special-grade antimicrobials in the hospital, the use rate of various antibiotics except linezolid, amphotericin B and posaconazole, and the proportion of special-grade antimicrobials used in the hospital have all shown a downward trend year by year ( P<0.01). The total usage rate and total AUD of special-grade antimicrobials in ICU showed a decreasing trend year by year ( χ2=343.514, P<0.01, β=-0.963, P=0.002). Conclusion:The information management system for special-grade antimicrobial can effectively reduce the utilization rate and AUD of most special-grade antibiotics in hospitalized patients including ICU, and has a good clinical application value in antimicrobial stewardship.