BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Objective:This article studies the abilities and quality that medical technical managers should possess and provides a reference for promoting the professional training and development of medical technical managers.Methods:The data were obtained through semi-structured interviews and literature collection. The interview subjects were 20 scientific researchers with transformation projects and 10 management staffs with technical manager certificates in medical colleges. The documents are 6 articles related to ″technical manager capabilities″ collected on open academic platforms. Grounded theory was used to code and analyze above data.Results:After three-level coding and combining with the iceberg competency model, the knowledge, skills, self-awareness, traits and motivation of medical technology managers were sorted out, totalling 5 core categories, 10 main categories, and 50 initial categories, to construct a competency model for medical technology managers.Conclusions:Based on the complex knowledge structure and high occupational requirements of medical technology managers, policy insights such as systematic knowledge training, raising skill requirements in practice, and enriching assessment standards and communication channels are proposed.

OBJECTIVES: Prolonged invasive mechanical ventilation is associated with increased risks of severe complications such as retinopathy of prematurity and bronchopulmonary dysplasia. Although neonatal intensive care unit (NICU) follow the principle of early extubation, extubation failure rates remain high, and reintubation may further increase the risk of adverse outcomes. This study aims to identify risk factors and short-term prognosis associated with first extubation failure in neonates, to provide evidence for effective clinical intervention strategies. METHODS: Clinical data of neonates who received invasive ventilation in the NICU of Children's Hospital of Nanjing Medical University from January 1, 2019, to December 31, 2021, were retrospectively collected. Neonates were divided into a successful extubation group and a failed extubation group based on whether reintubation occurred within 72 hours after the first extubation. Risk factors and short-term outcomes related to extubation failure were analyzed. RESULTS: A total of 337 infants were included, with 218 males (64.69%). Initial extubation failed in 34 (10.09%) infants. Compared with the successful extubation group, the failed extubation group had significantly lower gestational age [(31.37±5.14) weeks vs (34.44±4.07) weeks], age [2.5 (1.00, 8.25) h vs 5 (1.00, 22.00) h], birth weight [(1 818.97±1128.80) g vs (2 432.18±928.94) g], 1-minute Apgar score (6.91±1.90 vs 7.68±2.03), and the proportion of using mask oxygenation after extubation (21% vs 46%) (all P<0.05). Conversely, compared with the successful extubation group, the failed extubation group had significantly higher rates of vaginal delivery (59% vs 32%), caffeine use during mechanical ventilation (71% vs 38%), dexamethasone use at extubation (44% vs 17%), the highest positive end-expiratory pressure level within 72 hours post-extubation [6(5.00, 6.00) cmH₂O vs 5 (0.00, 6.00) cmH₂O] (1 cmH₂O=0.098 kPa), the highest FiO₂ within 72 hours post-extubation [(34.35±5.95)% vs (30.22±3.58)%], and duration of noninvasive intermittent positive pressure ventilation after extubation [0.5 (0.00, 42.00) hours vs 0 (0, 0) hours] (all P<0.05). Multivariate analysis identified gestational age <28 weeks (OR=5.570, 95% CI 1.866 to 16.430), age at NICU admission (OR=0.959, 95% CI 0.918 to 0.989), and a maximum FiO₂≥35% within 72 hours post-extubation (OR=4.541, 95% CI 1.849 to 10.980) as independent risk factors for extubation failure (all P<0.05). Additionally, the failed extubation group exhibited significantly higher incidences of necrotizing enterocolitis grade II or above, moderate-to-severe bronchopulmonary dysplasia, severe bronchopulmonary dysplasia, retinopathy of prematurity, treatment abandonment due to poor prognosis, and discharge on home oxygen therapy (all P<0.05). Total hospital length of stay and total hospitalization costs were also significantly increased in the failed extubation group (all P<0.05). CONCLUSIONS Gestational age <28 weeks, younger age at NICU admission, and FiO₂≥35% after extubation are high-risk factors for first extubation failure in neonates. Extubation failure markedly increases the risk of adverse clinical outcomes.
Humans ; Infant, Newborn ; Male ; Female ; Airway Extubation/adverse effects* ; Risk Factors ; Retrospective Studies ; Respiration, Artificial/methods* ; Intensive Care Units, Neonatal ; Prognosis ; Gestational Age ; Bronchopulmonary Dysplasia ; Infant, Premature ; Treatment Failure ; Intubation, Intratracheal

Objective:This article studies the abilities and quality that medical technical managers should possess and provides a reference for promoting the professional training and development of medical technical managers.Methods:The data were obtained through semi-structured interviews and literature collection. The interview subjects were 20 scientific researchers with transformation projects and 10 management staffs with technical manager certificates in medical colleges. The documents are 6 articles related to ″technical manager capabilities″ collected on open academic platforms. Grounded theory was used to code and analyze above data.Results:After three-level coding and combining with the iceberg competency model, the knowledge, skills, self-awareness, traits and motivation of medical technology managers were sorted out, totalling 5 core categories, 10 main categories, and 50 initial categories, to construct a competency model for medical technology managers.Conclusions:Based on the complex knowledge structure and high occupational requirements of medical technology managers, policy insights such as systematic knowledge training, raising skill requirements in practice, and enriching assessment standards and communication channels are proposed.

Purpose/Significance To analyze the characteristics of organ representation of anatomical ontologies,and to provide ref-erences for the research and construction of ontology in other fields.Method/Process The similarities and differences of three mainstream anatomical ontologies of SNOMED CT(SCT),Uberon and the foundational model of anatomy ontology(FMA)in terms of organ classifi-cation methods and term mapping are compared.Result/Conclusion Among the three main types of anatomical ontologies,SCT and Uberon are mainly classified according to the function of organs,while FMA is mainly classified according to the anatomical morphology of organs.The concept of organs in FMA and Uberon is the same as the concept of entire organs in SCT,and the representation forms of paired organs in SCT,Uberon and FMA are similar.

Epilepsy is a widespread neurological disease, which can be caused by any pathological process that may affect the structure and function of the brain.It encompasses a spectrum of pathologies rather than a singular entity.Early detection and diagnosis is the key to controlling the progression of epilepsy and improving the prognosis.Magnetic resonance imaging (MRI) is a clinically recognized method for the examination of epilepsy because of its non-ionizing radiation damage and excellent soft tissue resolution and spatial resolution.With the upgrading of MRI equipment and the open application of new imaging technologies, such as multimodal MRI that integrates multiple magnetic resonance sequences, its multi-parameter imaging and high spatial resolution have completely changed the ability to detect lesions, making significant progress in understanding epilepsy from the anatomical structure, molecular level, and biochemical metabolism.This article reviews the advances in the application of multimodal MRI technology in childhood epilepsy.

Objective To explore the differences of bone age of radius,ulna,metacarpophalangeal and carpal bones in children with different physiques.Methods Radiographs of children's wrists aged between 4 and 12 years were collected.The bone age of radius,ulna,metacarpophalangeal,and carpal bones were assessed using the Chinese Children's Bone Age Score,and the difference between the two bone ages(the former minus the latter)was recorded.According to gender,age,and physical grouping,the physical group was divided into normal and abnormal groups.The abnormal group was further divided into thin,overweight,and obese groups.A comparative analysis was conducted to determine the differences in bone age between normal and abnormal groups for both males and females at all ages.Results A total of 3 028 children were included,and the differences between the two bone age results for normal boys aged 7-12 years and normal girls aged 5-12 years were not statistically significant(P＞0.05).In boys,there was no significant difference in bone age between the normal group and the thin group(P＞0.05),the difference in bone age between the normal and thin groups at the age of 5-6 years was greater than that between the overweight and obese groups,and the difference was statistically significant(P＜0.05),the difference in bone age between the normal group at 11-12 years and the thin group at 11 years was smaller than that between the overweight and obese groups(P＜0.05).The difference in bone age was smaller in the normal group than in the thin group at 6 years of age for girls(P＜0.05),and larger in the thin group than in the overweight and obese groups at 5 to 6 years old(P＜0.05).Conclusion The difference in bone age between the TW-C RUS series and TW-C C series bone age values is influenced by the child's gender,physique,and age.The difference in bone age between the majority of normal children and the thin group is not statistically significant,but differed from the overweight and obese groups at some ages,most are the overweight and obese boys.

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Objective:To screen out nociceptive neuron-related genes associated with the prognosis of lung adenocarcinoma(LUAD)patients through bioinformatics analysis and construct a prognostic risk assessment model for LUAD based on these genes,as well as to further explore the correlation between this model and tumor immune microenvironment of LUAD patients.Methods:Differentially expressed genes between LUAD tumor tissues and normal lung tissues were obtained from the TCGA database,and compared with 117 known nociceptive neuron-related genes to screen out candidate genes significantly associated with the prognosis of LUAD patients.The Lasso algorithm was used to refine the candidate genes to obtain key genes for constructing the LUAD prognostic risk assessment model.Based on this model,LUAD patients in the TCGA database were divided into high-risk and low-risk groups according to the median of the prognostic risk score.The specificity and sensitivity of the model were assessed using the receiver operating characteristic(ROC)curve,and the external dataset GSE31210 was used to verify the effectiveness of this model in predicting the prognosis of LUAD patients.Additionally,univariate and multivariate COX regression analyses were conducted to compare the independent predictive value of the model and clinical parameters for the prognosis of LUAD patients.Finally,immune infiltration analysis was performed to compare the differences in immune function between high-risk and low-risk LUAD patients,further revealing the potential link between nociceptive neuron-related genes and tumor immunity.Results:A prognostic risk assessment model for LUIAD patients based on 14 nociceptive neuron-related genes was successfully constructed,which was effective in predicting the prognosis of LUAD patients(P<0.001).Further analysis revealed that tumor immune cell infiltration in high-risk LUAD patients was significantly lower than that in low-risk LUAD patients.Conclusion:This study confirms a significant association between nociceptive neuron-related genes and LUAD,and suggesting that injury stimulation can affect LUAD progression by mediating changes in the tumor immune microenvironment.This finding provides a favorable theoretical support for the development of nociceptive neurons and their receptors as future drug targets for LUAD.

Objective:To screen out nociceptive neuron-related genes associated with the prognosis of lung adenocarcinoma(LUAD)patients through bioinformatics analysis and construct a prognostic risk assessment model for LUAD based on these genes,as well as to further explore the correlation between this model and tumor immune microenvironment of LUAD patients.Methods:Differentially expressed genes between LUAD tumor tissues and normal lung tissues were obtained from the TCGA database,and compared with 117 known nociceptive neuron-related genes to screen out candidate genes significantly associated with the prognosis of LUAD patients.The Lasso algorithm was used to refine the candidate genes to obtain key genes for constructing the LUAD prognostic risk assessment model.Based on this model,LUAD patients in the TCGA database were divided into high-risk and low-risk groups according to the median of the prognostic risk score.The specificity and sensitivity of the model were assessed using the receiver operating characteristic(ROC)curve,and the external dataset GSE31210 was used to verify the effectiveness of this model in predicting the prognosis of LUAD patients.Additionally,univariate and multivariate COX regression analyses were conducted to compare the independent predictive value of the model and clinical parameters for the prognosis of LUAD patients.Finally,immune infiltration analysis was performed to compare the differences in immune function between high-risk and low-risk LUAD patients,further revealing the potential link between nociceptive neuron-related genes and tumor immunity.Results:A prognostic risk assessment model for LUIAD patients based on 14 nociceptive neuron-related genes was successfully constructed,which was effective in predicting the prognosis of LUAD patients(P<0.001).Further analysis revealed that tumor immune cell infiltration in high-risk LUAD patients was significantly lower than that in low-risk LUAD patients.Conclusion:This study confirms a significant association between nociceptive neuron-related genes and LUAD,and suggesting that injury stimulation can affect LUAD progression by mediating changes in the tumor immune microenvironment.This finding provides a favorable theoretical support for the development of nociceptive neurons and their receptors as future drug targets for LUAD.