Objective:To investigate the correlationship between an artificial intelligence-based e-Boston bowel preparation scale (e-BBPS) system score and the adenoma miss rate.Methods:Colonoscopy images of 4 373 patients at the Endoscopy Center of Renmin Hospital of Wuhan University from December 21, 2017 to December 31, 2019 were collected for model training. Patients who underwent colonoscopy at the Eighth Affiliated Hospital of Sun Yat-sen University from October 8, 2021 to November 9, 2022 were prospectively included. Patient's bowel preparation was evaluated by the e-BBPS system and endoscopists based on BBPS score. If both the endoscopists and e-BPPS system believed that the bowel preparation was sufficient, the patient immediately proceeded to a second colonoscopy. Otherwise, the patient underwent bowel preparation again. The differences in adenoma and polyp miss rate between the qualified group (e-BBPS system score ≤3) and the unqualified group (e-BBPS system score >3) were compared.Results:The adenoma miss rate in the qualified group was significantly lower than that in the unqualified group [26.72% (62/232) VS 42.53% (37/87), χ2=7.384， P=0.007, OR=2.029 (95% CI: 1.212-3.396)], and the polyp miss rate in the qualified group was significantly lower than that in the unqualified group [27.28% (195/702) VS 41.24% (113/274), χ2=16.539， P<0.001, OR=1.825 (95% CI: 1.363-2.443)]. Conclusion:The deep learning-based e-BBPS system demonstrates accuracy and reliability in bowel preparation assessment, offering potential to standardize the process of evaluating bowel preparation and reduce missed lesions.

Objective:To analyze the clinical significance of molecular classification and hereditary phenotype in endometrial carcinoma (EC) based on high throughput sequencing (NGS).Methods:97 EC samples were collected retrospectively from December 2019 to October 2022 in China-Japan Friendship Hospital. NGS technique was used to analyze the molecular classification, POLE hypermutation, microsatellite high Instability/mismatch repair dysfunction (MSI-H/MMRd), P53 protein abnormality (P53 abn), and non-specific molecular profile (NSMP). Lynch syndrome related genes and BRCA1/2 genes were detected by NGS and their genetic characteristics were analyzed. Results:Of the 97 EC cases, 77 were endometrial adenocarcinoma and 20 were other pathological subtypes. The proportions of the four molecular subtypes were 9.3% (9/97) POLE hypermutation, 16.5% (16/97) MSI-H, 17.5% (17/97) P53 abn and 56.7% (55/97) NSMP, respectively. There were significant differences in age, histological type, lymph node metastasis, pathological stage and other parameters among the four molecular types ( P＜0.05). 8.2% (8/97) were multiple molecular typing and four multiple molecular typings detected, including POLEmut-MSI-H, POLEmut-P53abn, MSI-H-P53abn, P53abn-P53abn, which accounted for 1.0% (1/97), 3.1% (3/97), 1.0% (1/97) and 3.1% (3/97), respectively. The consistent rate of MSI-H and MMR protein expression was 92.9% ( Kappa=0.818, P＜0.001). The coincidence rate between TP53 gene sequencing and P53 protein expression was 88.9% ( Kappa=0.661, P＜0.001). In MSI-H type, 25.0% (4/16) were diagnosed as Lynch syndrome, and 75.0% (12/16) were diagnosed as Lynch like syndrome. 7.2% (7/97) BRCA2 somatic variation was detected, while BRCA1/2 germline variation was not detected in 97 cases. Conclusions:EC molecular classification has feasibility and clinical value. High throughput sequencing can detect low frequency mutations of TP53 gene, suggesting that it can provide more accurate molecular information and more accurate molecular typing effect. It is suggested to further detect Lynch syndrome related genes in patients with MSI-H, so as to carry out genetic management for patients and their families and achieve better therapeutic effect.

Objective:To investigate the correlationship between an artificial intelligence-based e-Boston bowel preparation scale (e-BBPS) system score and the adenoma miss rate.Methods:Colonoscopy images of 4 373 patients at the Endoscopy Center of Renmin Hospital of Wuhan University from December 21, 2017 to December 31, 2019 were collected for model training. Patients who underwent colonoscopy at the Eighth Affiliated Hospital of Sun Yat-sen University from October 8, 2021 to November 9, 2022 were prospectively included. Patient's bowel preparation was evaluated by the e-BBPS system and endoscopists based on BBPS score. If both the endoscopists and e-BPPS system believed that the bowel preparation was sufficient, the patient immediately proceeded to a second colonoscopy. Otherwise, the patient underwent bowel preparation again. The differences in adenoma and polyp miss rate between the qualified group (e-BBPS system score ≤3) and the unqualified group (e-BBPS system score >3) were compared.Results:The adenoma miss rate in the qualified group was significantly lower than that in the unqualified group [26.72% (62/232) VS 42.53% (37/87), χ2=7.384， P=0.007, OR=2.029 (95% CI: 1.212-3.396)], and the polyp miss rate in the qualified group was significantly lower than that in the unqualified group [27.28% (195/702) VS 41.24% (113/274), χ2=16.539， P<0.001, OR=1.825 (95% CI: 1.363-2.443)]. Conclusion:The deep learning-based e-BBPS system demonstrates accuracy and reliability in bowel preparation assessment, offering potential to standardize the process of evaluating bowel preparation and reduce missed lesions.

Objective:To analyze the clinical significance of molecular classification and hereditary phenotype in endometrial carcinoma (EC) based on high throughput sequencing (NGS).Methods:97 EC samples were collected retrospectively from December 2019 to October 2022 in China-Japan Friendship Hospital. NGS technique was used to analyze the molecular classification, POLE hypermutation, microsatellite high Instability/mismatch repair dysfunction (MSI-H/MMRd), P53 protein abnormality (P53 abn), and non-specific molecular profile (NSMP). Lynch syndrome related genes and BRCA1/2 genes were detected by NGS and their genetic characteristics were analyzed. Results:Of the 97 EC cases, 77 were endometrial adenocarcinoma and 20 were other pathological subtypes. The proportions of the four molecular subtypes were 9.3% (9/97) POLE hypermutation, 16.5% (16/97) MSI-H, 17.5% (17/97) P53 abn and 56.7% (55/97) NSMP, respectively. There were significant differences in age, histological type, lymph node metastasis, pathological stage and other parameters among the four molecular types ( P＜0.05). 8.2% (8/97) were multiple molecular typing and four multiple molecular typings detected, including POLEmut-MSI-H, POLEmut-P53abn, MSI-H-P53abn, P53abn-P53abn, which accounted for 1.0% (1/97), 3.1% (3/97), 1.0% (1/97) and 3.1% (3/97), respectively. The consistent rate of MSI-H and MMR protein expression was 92.9% ( Kappa=0.818, P＜0.001). The coincidence rate between TP53 gene sequencing and P53 protein expression was 88.9% ( Kappa=0.661, P＜0.001). In MSI-H type, 25.0% (4/16) were diagnosed as Lynch syndrome, and 75.0% (12/16) were diagnosed as Lynch like syndrome. 7.2% (7/97) BRCA2 somatic variation was detected, while BRCA1/2 germline variation was not detected in 97 cases. Conclusions:EC molecular classification has feasibility and clinical value. High throughput sequencing can detect low frequency mutations of TP53 gene, suggesting that it can provide more accurate molecular information and more accurate molecular typing effect. It is suggested to further detect Lynch syndrome related genes in patients with MSI-H, so as to carry out genetic management for patients and their families and achieve better therapeutic effect.

Objective:To understand the satisfaction evaluation of contracted residents with " Internet plus" family doctor services and to explore its influencing factors.Methods:From November to December 2021, a stratified random sampling method was used to select 360 contracted residents who had utilized " Internet plus" family doctor services from community health service centers or township health clinics in various counties, cities, or districts of a city in Shandong Province for on-site questionnaire surveys. The purpose was to understand their awareness and satisfaction with the " Internet plus" family doctor services. At the same time, key informant interviews were conducted with contracted residents according to the principle of intensity sampling and information saturation, to collect their opinions and suggestions on the implementation process and model construction of " Internet plus" family doctor services. Descriptive analysis was performed on the data, and a binary logistic regression model was used to analyze the factors affecting the satisfaction of contracted residents with " Internet plus" family doctor services.Results:352 valid questionnaires were obtained. Among the respondents, 108 (30.6%) were very familiar or relatively familiar with the " Internet plus" family doctor service policy, and 251 (71.3%) expressed a high level of satisfaction with the overall " Internet plus" family doctor service. Gender, monthly income status, frequency of participation in health education activities, and satisfaction with the doctor′s daily service attitude, medical technical level, medical service charge level, and the level of communication between the service team and family members were factors affecting the satisfaction of contracted residents with " Internet plus" family doctor services ( P<0.05). Interview results showed that 38 people (95.0%) believed that there were issues with the current implementation of " Internet plus" family doctor services in China, such as the lack of an effective policy support environment, the need to improve the publicity and mobilization effects of contracting institutions, poor service cognition levels among the population, concerns about service quality, misunderstandings about internet-related concepts, network " panic" caused by electronic fraud phenomena, and cultural level differences among the elderly that limited the use of services. Conclusions:The overall satisfaction of contracted residents with the " Internet plus" family doctor services was relatively good. Various factors affected the satisfaction evaluation of contracted residents. It is important to focus on the differences in service psychological perception among contracted residents with different demographic characteristics, strengthen the construction of service teams and service platforms, and improve the public′s cognition and participation in " Internet plus" family doctor services to promote the continuous development of " Internet plus" family doctor services.

Objective:To develop and evaluate metal artifact removal systems (MARSs) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images.Methods:A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05).Results:Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0 mm, 1.5 mm, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively ( F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively ( F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 ( F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 ( F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 ( F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 ( F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARSs. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions:Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.

Objective:To develop and evaluate metal artifact removal systems (MARS) based on deep learning to assess their effectiveness in removing artifacts caused by different thicknesses of metals in cone-beam CT (CBCT) images.Methods:A full-mouth standard model (60 mm×75 mm×110 mm) was three-dimensional (3D) printed using photosensitive resin. The model included a removable and replaceable target tooth position where cobalt-chromium alloy crowns with varying thicknesses were inserted to generate matched CBCT images. The artifacts resulting from cobalt-chromium alloys with different thicknesses were evaluated using the structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR). CNN-MARS and U-net-MARS were developed using a convolutional neural network and U-net architecture, respectively. The effectiveness of both MARSs were assessed through visualization and by measuring SSIM and PSNR values. The SSIM and PSNR values were statistically analyzed using one-way analysis of variance (α=0.05).Results:Significant differences were observed in the range of artifacts produced by different thicknesses of cobalt-chromium alloys (all P<0.05), with 1 mm resulting in the least artifacts. The SSIM values for specimens with thicknesses of 1.0, 1.5, and 2.0 mm were 0.916±0.019, 0.873±0.010, and 0.833±0.010, respectively ( F=447.89, P<0.001). The corresponding PSNR values were 20.834±1.176, 17.002±0.427, and 14.673±0.429, respectively ( F=796.51, P<0.001). After applying CNN-MARS and U-net-MARS to artifact removal, the SSIM and PSNR values significantly increased for images with the same thickness of metal (both P<0.05). When using the CNN-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.938±0.023, 0.930±0.029, and 0.928±0.020 ( F=2.22, P=0.112), while the PSNR values were 30.938±1.495, 30.578±2.154 and 30.553±2.355 ( F=0.54, P=0.585). When using the U-net-MARS for artifact removal, the SSIM values for 1.0, 1.5 and 2.0 mm were 0.930±0.024, 0.932±0.017 and 0.930±0.012 ( F=0.24, P=0.788), and the PSNR values were 30.291±0.934, 30.351±1.002 and 30.271±1.143 ( F=0.07, P=0.929). No significant differences were found in SSIM and PSNR values after artifact removal using CNN-MARS and U-net-MARS for different thicknesses of cobalt-chromium alloys (all P>0.05). Visualization demonstrated a high degree of similarity between the images before and after artifact removal using both MARS. However, CNN-MARS displayed clearer metal edges and preserved more tissue details when compared with U-net-MARS. Conclusions:Both the CNN-MARS and U-net-MARS models developed in this study effectively remove the metal artifacts and enhance the image quality. CNN-MARS exhibited an advantage in restoring tissue structure information around the artifacts compared to U-net-MARS.

BACKGROUND: Rheumatoid arthritis (RA), a chronic systemic autoimmune disease, is characterized by synovitis and progressive damage to the bone and cartilage of the joints, leading to disability and reduced quality of life. This study was a randomized clinical trial comparing the outcomes between withdrawal and dose reduction of tofacitinib in patients with RA who achieved sustained disease control. METHODS: The study was designed as a multicenter, open-label, randomized controlled trial. Eligible patients who were taking tofacitinib (5 mg twice daily) and had achieved sustained RA remission or low disease activity (disease activity score in 28 joints [DAS28] ≤3.2) for at least 3 months were enrolled at six centers in Shanghai, China. Patients were randomly assigned (1:1:1) to one of three treatment groups: continuation of tofacitinib (5 mg twice daily); reduction in tofacitinib dose (5 mg daily); and withdrawal of tofacitinib. Efficacy and safety were assessed up to 6 months. RESULTS: Overall, 122 eligible patients were enrolled, with 41 in the continuation group, 42 in the dose-reduction group, and 39 in the withdrawal group. After 6 months, the percentage of patients with a DAS28-erythrocyte sedimentation rate (ESR) of <3.2 was significantly lower in the withdrawal group than that in the reduction and continuation groups (20.5%, 64.3%, and 95.1%, respectively; P  < 0.0001 for both comparisons). The average flare-free time was 5.8 months for the continuation group, 4.7 months for the dose reduction group, and 2.4 months for the withdrawal group. CONCLUSION: Withdrawal of tofacitinib in patients with RA with stable disease control resulted in a rapid and significant loss of efficacy, while standard or reduced doses of tofacitinib maintained a favorable state. TRIAL REGISTRATION Chictr.org, ChiCTR2000039799.
Humans ; Quality of Life ; China ; Arthritis, Rheumatoid/drug therapy* ; Piperidines/therapeutic use* ; Treatment Outcome ; Antirheumatic Agents/therapeutic use* ; Pyrroles/therapeutic use*

Objective: To compare the diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3-tesla (3T) magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of visceral pleural surface invasion (VPSI). Visceral pleural invasion by non-small-cell lung cancer (NSCLC) can be classified into two types: PL1 (without VPSI), invasion of the elastic layer of the visceral pleura without reaching the visceral pleural surface, and PL2 (with VPSI), full invasion of the visceral pleura. Materials and Methods: Thirty-three patients with pathologically confirmed VPSI by NSCLC were retrospectively reviewed.Multidetector CT and contrast-enhanced 3T MRI with a free-breathing radial three-dimensional fat-suppressed volumetric interpolated breath-hold examination (VIBE) pulse sequence were compared in terms of the length of contact, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. Supplemental evaluation of the tumor-pleura interface (smooth versus irregular) could only be performed with MRI (not discernible on CT). Results: At the tumor-pleura interface, radial VIBE MRI revealed a smooth margin in 20 of 21 patients without VPSI and an irregular margin in 10 of 12 patients with VPSI, yielding an accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F-score for VPSI detection of 91%, 83%, 95%, 91%, 91%, and 87%, respectively. The McNemar test and receiver operating characteristics curve analysis revealed no significant differences between the diagnostic accuracies of CT and MRI for evaluating the contact length, angle of mass margin, or arch distance-to-maximum tumor diameter ratio as predictors of VPSI. Conclusion The diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3T MRI and CT were equal in terms of the contact length, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. The advantage of MRI is its clear depiction of the tumor-pleura interface margin, facilitating VPSI detection.

Objective: To compare the diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3-tesla (3T) magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of visceral pleural surface invasion (VPSI). Visceral pleural invasion by non-small-cell lung cancer (NSCLC) can be classified into two types: PL1 (without VPSI), invasion of the elastic layer of the visceral pleura without reaching the visceral pleural surface, and PL2 (with VPSI), full invasion of the visceral pleura. Materials and Methods: Thirty-three patients with pathologically confirmed VPSI by NSCLC were retrospectively reviewed.Multidetector CT and contrast-enhanced 3T MRI with a free-breathing radial three-dimensional fat-suppressed volumetric interpolated breath-hold examination (VIBE) pulse sequence were compared in terms of the length of contact, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. Supplemental evaluation of the tumor-pleura interface (smooth versus irregular) could only be performed with MRI (not discernible on CT). Results: At the tumor-pleura interface, radial VIBE MRI revealed a smooth margin in 20 of 21 patients without VPSI and an irregular margin in 10 of 12 patients with VPSI, yielding an accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F-score for VPSI detection of 91%, 83%, 95%, 91%, 91%, and 87%, respectively. The McNemar test and receiver operating characteristics curve analysis revealed no significant differences between the diagnostic accuracies of CT and MRI for evaluating the contact length, angle of mass margin, or arch distance-to-maximum tumor diameter ratio as predictors of VPSI. Conclusion The diagnostic performance of contrast-enhanced radial T1-weighted gradient-echo 3T MRI and CT were equal in terms of the contact length, angle of mass margin, and arch distance-to-maximum tumor diameter ratio. The advantage of MRI is its clear depiction of the tumor-pleura interface margin, facilitating VPSI detection.