Objective:To investigate the value of an MRI and digital pathology images based omics nomogram for the prediction of recurrence risk in soft tissue sarcoma (STS).Methods:This was a retrospective cohort study. From January 2016 to March 2021, 192 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled, among which 112 patients in the Laoshan campus were enrolled as training set, and 80 patients in the Shinan campus were enrolled as validation set. The patients were divided into recurrence group ( n=87) and no recurrence group ( n=105) during follow-up. The clinical and MRI features of patients were collected. The radiomics features based on fat saturated T 2WI images and pathomics features based on digital pathology images of the lesions were extracted respectively. The clinical model, radiomics model, pathomics model, radiomics-pathomics combined model, and omics nomogram which combined the optimal prediction model and the clinical model were established by multivariate Cox regression analysis. The concordance index (C index) and time-dependent area under the receiver operating characteristic curve (t-AUC) were used to evaluate the performance of each model in predicting STS postoperative recurrence. The DeLong test was used for comparison of t-AUC between every two models. The X-tile software was used to determine the cut-off value of the omics nomogram, then the patients were divided into low risk ( n=106), medium risk ( n=64), and high risk ( n=22) groups. Three groups′ cumulative recurrence-free survival (RFS) rates were calculated and compared by the Kaplan-Meier survival curve and log-rank test. Results:The performance of the radiomics-pathomics combined model was superior to the radiomics model and pathomics model, with C index of 0.727 (95% CI 0.632-0.823) and medium t-AUC value of 0.737 (95% CI0.584-0.891) in the validation set. The omics nomogram was established by combining the clinical model and the radiomics-pathomics combined model, with C index of 0.763 (95% CI 0.685-0.842) and medium t-AUC value of 0.783 (95% CI0.639-0.927) in the validation set. The t-AUC value of omics nomogram was significantly higher than that of clinical model, TNM model, radiomics model, and pathomics model in the validation set ( Z=3.33, 2.18, 2.08, 2.72, P=0.001, 0.029, 0.037, 0.007). There was no statistical difference in t-AUC between the omics nomogram and radiomics-pathomics combined model ( Z=0.70, P=0.487). In the validation set, the 1-year RFS rates of STS patients in the low, medium, and high recurrence risk groups were 92.0% (95% CI 81.5%-100%), 55.9% (95% CI 40.8%-76.6%), and 37.5% (95% CI 15.3%-91.7%). In the training and validation sets, there were statistically significant in cumulative RFS rates among the low, medium, and high groups of STS patients (training set χ2=73.90, P<0.001; validation set χ2=18.70, P<0.001). Conclusion:The omics nomogram based on MRI and digital pathology images has favorable performance for the prediction of STS recurrence risk.

Objective To observe the value of multiparametric MRI-based radiomics model and deep learning(DL)model for distinguishing benign and malignant myxoid soft tissue tumors(MSTT).Methods A total of 141 MSTT patients confirmed with pathology were retrospectively collected.The patients were randomly divided into training set(n=98,including 51 cases of malignant MSTT and 47 cases of benign MSTT)and test set(n=43,including 22 cases of malignant MSTT and 21 cases of benign MSTT)at the ratio of 7∶3.Based on T1WI and fat suppression(FS)-T2WI in training set,radiomics features and DL features were extracted and selected,then a radiomics model and a DL model were constructed,respectively.Receiver operating characteristic(ROC)curves,calibration curves and decision curves were drawn,and the discrimination,calibration and net benefit of these 2 models were compared.Results In training set,the radiomics model for differentiating benign and malignant MSTT was constructed according to 9 optimal radiomics features,including 2 first order features,1 shape feature,3 gray level co-occurrence matrix features,1 gray level dependence matrix feature and 2 gray level size zone matrix features,while DL model was built based on 7 optimal DL features.In test set,the area under the ROC curve of radiomics model and DL model was 0.758 and 0.911,respectively,the latter was higher than the former(P=0.017).Both models had good calibration,and DL model had higher overall net benefit.Conclusion Compared with radiomics model,DL model based on MRI had better ability to differentiating benign and malignant MSTT,also higher overall net benefit.

OBJECTIVE: To validate the effectiveness of a novel comprehensive classification for intertrochanteric fracture (ITF). METHODS: The study included 616 patients with ITF, including 279 males (45.29%) and 337 females (54.71%); the age ranged from 23 to 100 years, with an average of 72.5 years. Two orthopaedic residents (observers Ⅰ and Ⅱ) and two senior orthopaedic surgeons (observers Ⅲ and Ⅳ) were selected to classify the CT imaging data of 616 patients in a random order by using the AO/Orthopaedic Trauma Association (AO/OTA) classification of 1996/2007 edition, the AO/OTA classification of 2018 edition, and the novel comprehensive classification method at an interval of 1 month. Kappa consistency test was used to evaluate the intra-observer and inter-observer consistency of the three ITF classification systems. RESULTS: The inter-observer consistency of the three classification systems evaluated by 4 observers twice showed that the 3 classification systems had strong inter-observer consistency. Among them, the κ value of the novel comprehensive classification was higher than that of the AO/OTA classification of 1996/2007 edition and 2018 edition, and the experience of observers had a certain impact on the classification results, and the inter-observer consistency of orthopaedic residents was slightly better than that of senior orthopaedic surgeons. The intra-observer consistency of two evaluations of three classification systems by 4 observers showed that the consistency of the novel comprehensive classification was better for the other 3 observers, except that the consistency of observer Ⅳ in the AO/OTA classification of 2018 version was slightly higher than that of the novel comprehensive classification. The results showed that the novel comprehensive classification has higher repeatability, and the intra-observer consistency of senior orthopaedic surgeons was better than that of orthopaedic residents. CONCLUSION The novel comprehensive classification system has good intra- and inter-observer consistency, and has high validity in the classification of CT images of ITF patients; the experience of observers has a certain impact on the results of the three classification systems, and those with more experiences have higher intra-observer consistency.
Male ; Female ; Humans ; Young Adult ; Adult ; Middle Aged ; Aged ; Aged, 80 and over ; Observer Variation ; Reproducibility of Results ; Hip Fractures/surgery* ; Tomography, X-Ray Computed/methods* ; Radiography

Objectives:To analyze the clinical features and prognosis of patients with medullary thyroid carcinoma combined with papillary thyroid carcinoma (combined carcinoma).Methods:The clinical data of 24 patients admitted to Tianjin Medical University Cancer Hospital from Nov 2012 to Dec 2019 were retrospectively analyzed. The treatment methods, pathological results, and prognosis of all patients were examined.Results:The results showed that combined carcinoma accounted for 10.0% (24/241) of all medullary thyroid carcinoma cases. In the combined cancer group, 45.8% (11/24) patients had lymph node metastasis, and the type of metastasis matched the largest lesion. There were no significant differences in gendex ratio ( χ2=0.164, P>0.05), age at onset ( t=1.381, P>0.05), maximum diameter of lesion ( Z=-1.733, P>0.05), multifocality ( χ2=2.695, P>0.05), and lymph node metastasis in the central ( χ2=1.625, P>0.05) and lateral neck regions ( χ2=1.537, P>0.05) between combined cancer patients and those with MTC alone. The median follow-up time for the 24 patients was 77.6 months. Local recurrence was observed in 2 cases, while no distant metastasis was found. There were no significant differences in disease-free survival, disease-specific survival, and overall survival between combined cancer and pure MTC groups (all P>0.05). Conclusion:The pathological characteristics and prognosis of medullary thyroid carcinoma combined with papillary thyroid carcinoma are similar to those of pure MTC. Therefore, clinical treatment decisions can be similar to pure MTC.

Objective:To evaluate postoperative calcitonin level as a prognostic marker in long-term follow-up of medullary thyroid carcinoma(MTC).Methods:Clinical data of 146 MTC cases treated at Tianjin Medical University Cancer Institute and Hospital from Jan 2011 to Dec 2019 were reviewed retrospectively. The relationship between postoperative calcitonin and disease-free survival was analyzed. According to the level of calcitonin six months after operation, patients were divided into normal level group and elevated group.Results:The median tumor size in those 146 cases was (1.78±1.22)cm, and 81 cases had lymph node metastasis. After 6 months of follow-up, 89 cases had normal calcitonin, with median tumor size of (1.63±1.20)cm, and 35 cases had lymph node metastasis . After a median follow-up of 56 months, 78 patients had normal calcitonin, 11 patients had biochemical relapse, 3 patients had structural relapse, and no patients died. 57 cases had a higher calcitonin ,median tumor size (1.97±1.22)cm, 46 cases had lymph node metastasis, 5 cases had distant metastasis, 18 cases had structural recurrence, and 7 patients died. Univariate analysis showed that lymph node metastasis, TNM stage, preoperative calcitonin, lymph node dissection and postoperative calcitonin were correlated with long-term disease-free survival (all P < 0.05). Multivariate analysis showed that postoperative calcitonin and TNM stage were an independent prognosis factor for disease-free survival in MTC patients (all P < 0.05). Conclusion:Postoperative calcitonin is a independent prognostic marker for long-term disease-free survival in MTC patients.

Objective:To investigate the surgical method and clinical effects of the modified proper digital artery island flap in repairing complex fingertip defects.Methods:A retrospective observational study was conducted. From January 2017 to December 2021, 15 patients (15 fingers) with complex fingertip defects, involving the pulp, nail bed, and lateral wall of the nail, who met the inclusion criteria were admitted into General Hospital of Northern Theater Command, including 11 males and 4 females, aged from 18 to 55 years. The area of the post debridement wound was from 2.5 cm×2.0 cm to 3.5 cm×3.5 cm, and all the wounds were repaired by using modified proper digital artery island flap (including 3 parts: main flap, tongue-shaped flap, and triangular flap), of which the main flap was used to cover the finger pulp defect, the tongue-shaped flap was used to cover the nail bed and the nail lateral wall defect, and the triangular flap was inserted into the edge of the finger pulp wound to cover the vessel pedicle. The range of the flap ranged from 3.0 cm×2.0 cm to 4.5 cm×3.0 cm. The wound at the donor site was repaired with full-thickness skin graft of the groin, and the donor site of the skin graft was sutured directly. After operation, the survival of the flap and skin graft as well as and the appearance of the affected finger were observed. During the follow-up, the fingertip morphology of the affected finger was observed, two-point discrimination distance of the affected finger pulp was measured, and the patients' satisfaction with the efficacy (including very satisfied, satisfied, and dissatisfied) was asked, and the affected finger function was evaluated by the total active movement (TAM) system evaluation standard recommended by American Academy for Surgery of Hand.Results:After operation, the main flaps and skin grafts in 15 patients all survived; but the incision at the edge of tongue-shaped flap in one patient healed poorly, and one patient developed venous stasis at the distal end of the tongue-shaped flap; the triangular flap at the pedicle was slightly bloated in the early postoperative period and became smooth after 2 to 3 months. Overall, two patients developed subcutaneous hematoma in their flaps. All the complications were healed by appropriate dressing change, suture removal, or compression bandaging. After operation, the appearance of the flap was full and formed a prominent fingertip shape. During the follow-up of 6 months to 5 years, the fingertips of the affected fingers were prominent and full; the two-point discrimination distance of the affected finger pulp was (8.6±1.4) mm; 8 patients were very satisfied with the efficacy, 6 patients were satisfied, and one patient was dissatisfied; the functional assessment of the affected fingers were all excellent.Conclusions:The modified proper digital artery island flap can repair complex fingertip defects involving the pulp, nail bed, and lateral wall of the nail. The operation is simple, and the shape and function of the fingertip are good after surgery.

Objective:To develop and validate a MRI-based radiomics nomogram combining with radiomics signature and clinical factors for the preoperative differentiation of benign parotid gland tumors (BPGT) and malignant parotid gland tumors (MPGT).Methods:From January 2015 to May 2020, 86 patients with parotid tumors confirmed by surgical pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 35 patients in the University of Hong Kong-Shenzhen Hospital from January 2013 to January 2020 were enrolled as independent external validation sets. The logistic regression was used to establish a clinical-factors model based on demographics and MRI findings. Radiomics features were extracted from preoperative T 1WI and fat-saturated T 2WI (fs-T 2WI), a radiomics signature model was constructed, and a radiomics score (Rad-Score) was calculated. A combined diagnostic model and nomogram combining with the Rad-score and independent clinical factors was constructed using multivariate logistic regression analysis. The receiver operating characteristic (ROC) analysis was used to evaluate the performance of each model and DeLong test was used for comparison of area under the ROC curve (AUC). Results:The logistic regression results showed that deep lobe involvement (OR=3.285, P=0.040) and surrounding tissue invasion (OR=15.919, P=0.013) were independent factors for MPGT and constructed the clinical-factors model. A total of 19 features were extracted from the joint T 1WI and fs-T 2WI to build the radiomics signature model. The combined diagnostic model and nomogram incorporating deep lobe involvement, surrounding tissue invasion and Rad-score were established. The AUCs of the clinical-factors model, radiomics signature model and combined diagnostic model for differentiating BPGT from MPGT for the training and validation sets were 0.758, 0.951, 0.953 and 0.752, 0.941 and 0.964 respectively. The AUCs of the radiomics signature model and the combined diagnostic model were significantly higher than those of the clinical-factors model for both training and validation sets (training set: Z=3.95, 4.31, both P<0.001; validation set: Z=2.16, 2.67, P=0.031, 0.008). There was no statistical difference in AUCs between the radiomics signature model and combined diagnostic model (training set: Z=0.39, P=0.697; validation set: Z=1.10, P=0.273). Conclusions:The MRI-based radiomics signature model and radiomics nomogram incorporating deep lobe involvement, surrounding tissue invasion, and Rad-score showed favorable predictive efficacy for differentiating BPGT from MPGT.

Objective:To investigate the value of a preoperatively MRI-based deep learning (DL) radiomics machine learning model to distinguish low-grade and high-grade soft tissue sarcomas (STS).Methods:From November 2007 to May 2019, 151 patients with STS confirmed by pathology in the Affiliated Hospital of Qingdao University were enrolled as training sets, and 131 patients in the Affiliated Hospital of Shandong First Medical University and the Third Hospital of Hebei Medical University were enrolled as external validation sets. According to the French Federation Nationale des Centres de Lutte Contre le Cancer classification (FNCLCC) system, 161 patients with FNCLCC grades Ⅰ and Ⅱ were defined as low-grade and 121 patients with grade Ⅲ were defined as high-grade. The hand-crafted radiomic (HCR) and DL radiomic features of the lesions were extracted respectively. Based on HCR features, DL features, and HCR-DL combined features, respectively, three machine-learning models were established by decision tree, logistic regression, and support vector machine (SVM) classifiers. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each machine learning model and choose the best one. The univariate and multivariate logistic regression were used to establish a clinical-imaging factors model based on demographics and MRI findings. The nomogram was established by combining the optimal radiomics model and the clinical-imaging model. The AUC was used to evaluate the performance of each model and the DeLong test was used for comparison of AUC between every two models. The Kaplan-Meier survival curve and log-rank test were used to evaluate the performance of the optimal machine learning model in the risk stratification of progression free survival (PFS) in STS patients.Results:The SVM radiomics model based on HCR-DL combined features had the optimal predicting power with AUC values of 0.931(95%CI 0.889-0.973) in the training set and 0.951 (95%CI 0.904-0.997) in the validation set. The AUC values of the clinical-imaging model were 0.795 (95%CI 0.724-0.867) and 0.615 (95%CI 0.510-0.720), and of the nomogram was 0.875 (95%CI 0.818-0.932) and 0.786 (95%CI 0.701-0.872) in the training and validation sets, respectively. In validation set, the performance of SVM radiomics model was better than those of the nomogram and clinical-imaging models ( Z=3.16, 6.07; P=0.002,<0.001). Using the optimal radiomics model, there was statistically significant in PFS between the high and low risk groups of STS patients (training sets: χ2=43.50, P<0.001; validation sets: χ2=70.50, P<0.001). Conclusion:Preoperative MRI-based DL radiomics machine learning model has accurate prediction performance in differentiating the histopathological grading of STS. The SVM radiomics model based on HCR-DL combined features has the optimal predicting power and was expected to undergo risk stratification of prognosis in STS patients.

Objective:This study aimed to compare the detection efficacy of transrectal ultrasound-guided transrectal cognitive fusion targeted+ systematic prostate biopsy and transperineal cognitive fusion targeted + systematic biopsy in patients with suspected prostate cancer (PCa). In addition, the relative clinical characteristics of PCa were evaluated.Methods:A total of 385 patients with suspected prostate cancer in the affiliated hospital of Qingdao University from May 2019 to November 2019 were retrospectively analyzed. All patients met the prostate biopsy criterion, who underwent transrectal(n=275)and transperineal(n=110)prostate biopsy respectively. There were no significant differences of mean age [(70.7±7.3)years vs.(69.2±8.4) years], PSA [(55.12±116.96)ng/ml vs. (63.41±315.34)ng/ml], prostate volume [(55.96±35.26)ml vs. (64.35±55.99)ml] between two groups. According to preoperative prostate magnetic resonance imaging combined with intraoperative ultrasound, 2-4 needles targeted puncture of suspected lesion were performed, followed by 12 needle systematic prostate biopsy. The detection rate of prostate cancer between two biopsy ways were compared. The related factors of PCa including age, prostate volume and PSA level were collected for univariable and multivariable logistic analysis. The cancer detection rate was compared and logistic regression was used to assess the impact of patient characteristics on PCa detection.Results:For all patients, the detection rate with cancer between transrectal group and transperineal group were 121/275(40.0%) and 67/110(60.9%), respectively. The transperineal group detected a higher rate of PCa ( P=0.003)and more clinically significant prostate cancers (csPCa) (54.6% vs.36.7%, P=0.001) than that of the transrectal group, there were significant differences between two groups ( P<0.05). Univariate and multivariate logistic regression analysis revealed that PSA( OR=1.025, P=0.001) and prostate volume( OR=0.984, P=0.001)were two independent factors for the detection rate of prostate cancer between two biopsy ways( P<0.05). The effect of age on the detection rate of PCa in the transperieal group was significantly lower than that of the transrectal group( OR=0.037, P=0.238 vs. OR=0.053, P=0.002). Conclusion:The transperieal biopsy could find more PCa than the transrectal biopsy. PSA level and prostate volume could affect the detection rate of cancer between two prostate biopsy ways.

The fall armyworm (FAW), Spodoptera frugiperda, is a destructive pest native to America and has recently become an invasive insect pest in China. Because of its rapid spread and great risks in China, understanding of FAW genetic background and pesticide resistance is urgent and essential to develop effective management strategies. Here, we assembled a chromosome-level genome of a male FAW (SFynMstLFR) and compared re-sequencing results of the populations from America, Africa, and China. Strain identification of 163 individuals collected from America, Africa and China showed that both C and R strains were found in the American populations, while only C strain was found in the Chinese and African populations. Moreover, population genomics analysis showed that populations from Africa and China have close relationship with significantly genetic differentiation from American populations. Taken together, FAWs invaded into China were most likely originated from Africa. Comparative genomics analysis displayed that the cytochrome p450 gene family is extremely expanded to 425 members in FAW, of which 283 genes are specific to FAW. Treatments of Chinese populations with twenty-three pesticides showed the variant patterns of transcriptome profiles, and several detoxification genes such as AOX, UGT and GST specially responded to the pesticides. These findings will be useful in developing effective strategies for management of FAW in China and other invaded areas.
Animals ; China ; Genomics ; Humans ; Male ; Pesticides ; Spodoptera/genetics* ; Transcriptome