Objective To introduce an innovative technique, the "balance-shaped sternal elevation device" and its application in the subxiphoid uniportal video-assisted thoracoscopic surgery (VATS) for anterior mediastinal masses resection. Methods Patients who underwent single-port thoracoscopic assisted anterior mediastinal tumor resection through the xiphoid process at the Department of Thoracic Surgery, West China Hospital, Sichuan University from May to June 2024 were included, and their clinical data were analyzed. Results A total of 7 patients were included, with 3 males and 4 females, aged 28-72 years. The diameter of the tumor was 1.9-17.0 cm. The operation time was 62-308 min, intraoperative blood loss was 5-100 mL, postoperative chest drainage tube retention time was 0-9 days, pain score on the 7th day after surgery was 0-2 points, and postoperative hospital stay was 3-12 days. All patients underwent successful and complete resection of the masses and thymus, with favorable postoperative recovery. Conclusion The "balance-shaped sternal elevation device" effectively expands the retrosternal space, providing surgeons with satisfactory surgical views and operating space. This technique significantly enhances the efficacy and safety of minimally invasive surgery for anterior mediastinal masses, reduces trauma and postoperative pain, and accelerates patient recovery, demonstrating important clinical significance and application value.

Objective To introduce the modeling method of pendulum-like modified rat abdominal heart heterotopic transplantation model and evaluate the quality of the model. Methods An operator without transplantation experience performed 15 consecutive models, recorded the time of each step, changes in body weight and modified Stanford scores, and calculated the surgical success rate, postoperative 1-week survival rate and technical success rate. Ultrasound examinations was performed in 1 week postoperatively. Results The times for donor heart acquisition, donor heart processing, recipient preparation and transplantation anastomosis were (14.3±1.4) min, (3.5±0.6) min, (13.6±2.1) min and (38.3±5.2) min respectively. The surgical success rate was 87% (13/15), and the survival rate 1 week after operative was 100% (13/13). The improved Stanford score indicated a technical success rate of 92% (12/13), and the postoperative 1-week ultrasound examination showed that grafts with Stanford scores ≥3 had detectable pulsation and blood flow signals. Conclusions The pendulum-like modified rat abdominal heart heterotopic transplantation improved model further optimizes the operational steps with a high success rate and stable quality, may be chosen as a modeling option for basic research in heart transplantation in the future.

Objective To compare the efficacy and safety of video-assisted thoracoscopic surgery (VATS) thymectomy for the treatment of thymoma through subxiphoid uniportal approach using double sternum retractors, and subxiphoid and subcostal arch approach. Methods We retrospectively analyzed the clinical data of the patients diagnosed with thymoma who underwent VATS thymectomy from June 2023 to June 2024 in West China Hospital. Patients were categorized based on the surgical approach into two groups: a subxiphoid uniportal VATS thymectomy (SUVT) group and a subxiphoid and subcostal arch VATS thymectomy (SASAT) group. Comparisons were made between the two groups regarding surgical duration, intraoperative blood loss, postoperative drainage, thymoma size and location, and postoperative pain assessed using the visual analogue scale (VAS). Results The SUVT group consisted of 20 patients, including 11 males and 9 females, with an average age of (51.5±14.3) years. The SASAT group comprised 40 patients, including 26 males and 14 females, with an average age of (50.0±13.0) years. Compared to the SASAT group, the SUVT group had significantly larger thymomas [ (5.9±2.7) cm vs. (4.2±2.1) cm, P=0.010] and a higher proportion of neoplasms located in the superior mediastinum (30.0% vs. 2.5%, P=0.007). Additionally, the VAS pain scores on postoperative days 3, 7, and 30 were significantly lower in the SUVT group compared to the SASAT group (P<0.05). There were no statistical differences between the two groups in demographic characteristics, operative time, intraoperative blood loss, duration and volume of postoperative drainage, length of postoperative hospital stay, or the VAS pain score on the first postoperative day. Conclusion SUVT using double sternum retractors significantly reduces postoperative pain and provides superior efficacy in the resection of larger thymomas or those situated in the superior mediastinum.

Objective:To explore the effect of accurately localized mini anterolateral thigh perforator flap in repairing medium-sized skin and soft tissue defects in fingers.Methods:The study was a retrospective observational study. From December 2019 to September 2022, 15 patients with medium-sized skin and soft tissue defects who met the inclusion criteria in fingers were admitted to the Second Affiliated Hospital of Wenzhou Medical University, including 12 males and 3 females, aged 23 to 62 years. After debridement, the wounds were all accompanied by exposed tendons, bones, vessels and nerves, with an area from 4.0 cm×3.0 cm to 8.0 cm×3.5 cm. Computed tomography angiography and color Doppler ultrasonography examinations were performed on both lower limbs of the patient before surgery to accurately locate the anterolateral thigh perforators. When the flap with area from 6.0 cm×3.0 cm to 11.0 cm×4.0 cm was harvested, the flap was thinned. The artery and vein perforators of the flap were anastomosed respectively with the digital artery and dorsal metacarpal vein. If there was avulsion injury, infection, or burn in the recipient area, the main arterial and veinous vessels carried by the skin flap was anastomosed with the radial artery and accompanying vein. The lateral thigh cutaneous nerve carried by the flap was anastomosed with the stump of the digital nerve. The types of perforators of the lateral thigh artery were observed during operation and compared with the location of the vessels before operation. After operation, the survival and adverse complication of the flap were closely observed. During follow-up, the skin flap color, texture, and shape were observed; the wound healing in donor area was observed. At the last follow-up, the two-point discriminative distance of the affected finger pulp was measured, and the function of the affected finger was evaluated using the trial standard for the evaluation of functions of upper limbs of Hand Surgery Society of Chinese Medical Association, and the interphalangeal joint movement of the affected finger was observed; the patients' complaints about the adverse effects of flap resection on lower limbs were recorded.Results:During the operation, it was observed that the perforators of the flaps in 11 patients were the descending branch of the lateral circumflex thigh artery, in two patients, the perforators of skin flaps were the oblique branch of the lateral thigh artery, and the perforators in another two patients were the transverse branch of the lateral circumflex thigh artery, which were consistent with the preoperative vascular localization. After operation, all flaps survived without vascular crisis and infection. The patients were followed up for 6-12 months, the flaps had excellent color, texture, and appearance; only linear scars remained on the donor wound. At the last follow-up, the two-point discrimination distance in the finger pulp was 7-11 mm; the affected finger function was rated as excellent in 6 cases, good in 6 cases, and fair in 3 cases; the flexion and extension function of the finger was not affected; two patients complained of numbness in the lateral thigh after excision of the skin flap, and the other 13 patients had no complain of adverse complaints.Conclusions:The perforating branch in lateral thigh region can be accurately located by computed tomography angiography and color Doppler ultrasonography, accurate positioning of perforators before operation can reduce the damage to the donor area during the incision of the flap, the appearance and function of the affected finger can be restored to the maximum extent by thinning the transplanted flap and rebuilding the finger sensation. Therefore, it is an effective and reliable way to repair the medium-sized skin and soft tissue defects of fingers with the mini thigh anterolateral perforator flap.

Bone organoids can simulate the complex structure and function of the bone tissues, which makes them a frontier technology in organoid researches. Bone organoids show a tremendous potential of applications in bone disease modeling, bone injury repair, and medicine screening. Although advancements have been made so far in constructing bone organoids with functional structures like mineralization, bone marrow, trabecular bone, callus, woven bone, etc, the researches in this field are confronted with numerous challenges such as lack of standardized construction strategies and unified evaluation criteria, which limits their further promotion and application. To standardize researches in bone organoids, the Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, the Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, the Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and the Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine organized related experts to formulate Expert consensus on the construction, evaluation, and application of bone organoids ( version 2024) based on an evidence-based approach. A total of 17 recommendations were put forth, aiming to standardize researches and clinical applications of bone organoids and enhance their value in scientific research and clinical practice.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective To establish a deep learning model for testing the feasibility of combining magnetic resonance imaging(MRI)deep learning features with clinical features for preoperative prediction of cytokeratin 19(CK19)status of hepatocellular carcinoma(HCC).Methods A retrospective experiment was conducted based on the data of 116 HCC patients with confirmed CK19 status.A single sequence multi-scale feature fusion deep learning model(MSFF-IResnet)and a multi-scale and multi-modality feature fusion model(MMFF-IResnet)were established based on the hepatobiliary phase(HBP),diffusion weighted imaging(DWI)sequences of enhanced MRI images,and the clinical features significantly correlated with CK19 status.The classification performance of the models were evaluated to assess the effectiveness of the deep learning models for predicting CK19 status of HCC before surgery.Results Multivariate analysis showed that an increased neutrophil-to-lymphocyte ratio(P=0.029)and incomplete tumor capsule(P=0.028)were independent predictors of CK19 expression in HCC.The deep learning models improved by multi-scale feature fusion and multi-modality feature fusion methods achieved better classification results than the traditional machine learning models and baseline models,and the final MMFF-IResnet model showed the best classification performance with an AUC of 84.2%,an accuracy of 80.6%,a sensitivity of 80.1%and a specificity of 81.2%.Conclusion The multi-scale and multi-modality feature fusion model based on MRI and clinical parameters is capable of predicting CK19 status of HCC,demonstrating the feasibility of combining deep learning methods with MRI and clinical features for preoperative prediction of CK19 status.

Objective To develop a method for accurate identification of multiscale carotid plaques in ultrasound images.Methods We proposed a two-stage carotid plaque detection method based on deep convolutional neural network(SM-YOLO).A series of algorithms such as median filtering,histogram equalization,and Gamma transformation were used to preprocess the dataset to improve image quality.In the first stage of the model construction,a candidate plaque set was built based on the YOLOX_l target detection network,using multiscale image training and multiscale image prediction strategies to accommodate carotid artery plaques of different shapes and sizes.In the second stage,the Histogram of Oriented Gradient(HOG)features and Local Binary Pattern(LBP)features were extracted and fused,and a Support Vector Machine(SVM)classifier was used to screen the candidate plaque set to obtain the final detection results.This model was compared quantitatively and visually with several target detection models(YOLOX_l,SSD,EfficientDet,YOLOV5_l,Faster R-CNN).Results SM-YOLO achieved a recall of 89.44%,an accuracy of 90.96%,a F1-Score of 90.19%,and an AP of 92.70%on the test set,outperforming other models in all performance indicators and visual effects.The constructed model had a much shorter detection time than the Faster R-CNN model(only one third of that of the latter),thus meeting the requirements of real-time detection.Conclusion The proposed carotid artery plaque detection method has good performance for accurate identification of carotid plaques in ultrasound images.

Objective To establish a deep learning model for testing the feasibility of combining magnetic resonance imaging(MRI)deep learning features with clinical features for preoperative prediction of cytokeratin 19(CK19)status of hepatocellular carcinoma(HCC).Methods A retrospective experiment was conducted based on the data of 116 HCC patients with confirmed CK19 status.A single sequence multi-scale feature fusion deep learning model(MSFF-IResnet)and a multi-scale and multi-modality feature fusion model(MMFF-IResnet)were established based on the hepatobiliary phase(HBP),diffusion weighted imaging(DWI)sequences of enhanced MRI images,and the clinical features significantly correlated with CK19 status.The classification performance of the models were evaluated to assess the effectiveness of the deep learning models for predicting CK19 status of HCC before surgery.Results Multivariate analysis showed that an increased neutrophil-to-lymphocyte ratio(P=0.029)and incomplete tumor capsule(P=0.028)were independent predictors of CK19 expression in HCC.The deep learning models improved by multi-scale feature fusion and multi-modality feature fusion methods achieved better classification results than the traditional machine learning models and baseline models,and the final MMFF-IResnet model showed the best classification performance with an AUC of 84.2%,an accuracy of 80.6%,a sensitivity of 80.1%and a specificity of 81.2%.Conclusion The multi-scale and multi-modality feature fusion model based on MRI and clinical parameters is capable of predicting CK19 status of HCC,demonstrating the feasibility of combining deep learning methods with MRI and clinical features for preoperative prediction of CK19 status.

OBJECTIVE: To investigate the consistency and diagnostic performance of magnetic resonance imaging (MRI) for detecting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) and the validity of deep learning attention mechanisms and clinical features for MVI grade prediction. METHODS: This retrospective study was conducted among 158 patients with HCC treated in Shunde Hospital Affiliated to Southern Medical University between January, 2017 and February, 2020. The imaging data and clinical data of the patients were collected to establish single sequence deep learning models and fusion models based on the EfficientNetB0 and attention modules. The imaging data included conventional MRI sequences (T₁WI, T₂WI, and DWI), enhanced MRI sequences (AP, PP, EP, and HBP) and synthesized MRI sequences (T1mapping-pre and T1mapping-20 min), and the high-risk areas of MVI were visualized using deep learning visualization techniques. RESULTS: The fusion model based on T1mapping-20min sequence and clinical features outperformed other fusion models with an accuracy of 0.8376, a sensitivity of 0.8378, a specificity of 0.8702, and an AUC of 0.8501 for detecting MVI. The deep fusion models were also capable of displaying the high-risk areas of MVI. CONCLUSION The fusion models based on multiple MRI sequences can effectively detect MVI in patients with HCC, demonstrating the validity of deep learning algorithm that combines attention mechanism and clinical features for MVI grade prediction.
Humans ; Carcinoma, Hepatocellular ; Retrospective Studies ; Liver Neoplasms ; Magnetic Resonance Imaging ; Algorithms