Objective To investigate the clinical value of tumor-stroma ratio (TSR) in combination with KRAS, BRAF, NRAS, and microsatellite status for prognostic assessment of patients with colorectal cancer. Methods A total of 51 colorectal cancer cases meeting the inclusion and exclusion criteria were enrolled in this study. TSR levels were evaluated through optical microscopy. The KRAS/NRAS/BRAF mutation profiles and microsatellite status were determined in accordance with genetic testing results. Clinical data, pathological characteristics, and survival outcomes were systematically recorded. Results Among the 51 patients with colorectal cancer, 19 (37.3%) were categorized into the low stromal group and 32 (62.7%) into the high stromal group. Statistically significant differences were observed between the two groups in drug resistance, M stage, TNM stage, neural invasion, and microsatellite status (P<0.05). Compared with patients exhibiting high TSR, those with low TSR demonstrated significantly increased recurrence rates (5 vs. 21 cases, P=0.007), shortened disease-free survival (34.21 vs. 14.34 months, P=0.001), and reduced overall survival (38.79 vs. 23.09 months, P=0.021). Multivariate Cox regression analysis identified N stage, M stage, TNM stage, neural invasion, lymphovascular invasion, and TSR as independent risk factors for disease-free survival. N stage, M stage, neural invasion, lymphovascular invasion, and TSR emerged as independent prognostic factors for overall survival (P<0.05). Although the combined models of TSR with KRAS, NRAS, BRAF, and microsatellite status, respectively, demonstrated overall statistical significance (P<0.05), none of the dummy variables in these models reached individually statistical significance (P>0.05), and therefore cannot be considered independent prognostic factors. Conclusion TSR serves as an independent predictor of poor prognosis in advanced colorectal cancer, with patients exhibiting low TSR demonstrating a significantly higher risk of recurrence and metastasis than those with high TSR. For patients with colon cancer undergoing first-line palliative chemotherapy after postoperative recurrence, histopathological assessment of TSR in primary tumor sites holds prognostic value and may serve as a relevant factor for evaluating treatment resistance in clinical management.

OBJECTIVE To investigate the clinical characteristics of drug-induced liver injury （DILI） induced by glucagon- like peptide-1 receptor agonists （GLP-1RAs）， and to provide a reference for safe clinical medication. METHODS Using search terms such as “GLP-1”“GLP-1RAs”“semaglutide” “drug-induced liver injury”， relevant studies from PubMed， Embase， the Cochrane Library， CNKI， Wanfang Data and VIP were retrieved. Descriptive analysis was performed on cases of DILI induced by GLP-1RAs. RESULTS A total of 11 studies， comprising 11 patients， were included. Among them， 4 were male （36.4%） and 7 were female （63.6%）. Patient ages ranged from 17 to 64 years； 5 patients （45.5%） were between 50 and 65 years old. Six patients were treated for diabetes， and five for weight loss. Ten patients had underlying diseases. The shortest time to the onset of DILI was 5 days after medication， while the longest was approximately 180 days. The DILIs induced by GLP-1RAs were mainly hepatocellular injury type （6 cases）； severity levels included severe （3 cases）， moderate （6 cases）， and mild （2 cases）. Gastrointestinal symptoms and jaundice were the most common clinical manifestations. The association between DILI and GLP- 1RAs was assessed as “probable” in 10 cases and “possible” in 1 case. All 11 patients improved after drug discontinuation and （or） corresponding treatment. CONCLUSIONS DILI induced by GLP-1RAs is relatively concentrated in patients aged 50-65， with a higher incidence in females. The risk may be further increased in patients with underlying diseases. Clinical use of these agents should enhance pharmaceutical care， including identification of high-risk populations and patient education （especially symptom recognition）. When relevant symptoms appear， the drug should be discontinued immediately， with liver-protective therapy initiated when necessary， to ensure patient safety of drug use.

BACKGROUND: Severe stroke has high rates of mortality and morbidity. This study aimed to investigate the clinical course, causes of worsening, and outcomes of severe ischemic stroke. METHODS: This prospective, multicenter cohort study enrolled adult patients admitted ≤30 days after ischemic stroke from nine hospitals in China between September 2017 and December 2019. Severe stroke was defined as a score of ≥15 on the National Institutes of Health Stroke Scale (NIHSS). Clinical worsening was defined as an increase of 4 in the NIHSS score from baseline. Unfavorable functional outcome was defined as a modified Rankin scale score ≥3 at 3 months and 1 year after stroke onset, respectively. We performed Logistic regression to explore baseline features and reperfusion therapies associated with clinical worsening and functional outcomes. RESULTS: Among 4201 patients enrolled, 854 patients (20.33%) had severe stroke on admission. Of 3347 patients without severe stroke on admission, 142 (4.24%) patients developed severe stroke in hospital. Of 854 patients with severe stroke on admission, 33.95% (290/854) experienced clinical worsening (median time from stroke onset: 43 h, Q1-Q3: 20-88 h), with brain edema (54.83% [159/290]) as the leading cause; 24.59% (210/854) of these patients died by 30 days, and 81.47% (677/831) and 78.44% (633/807) had unfavorable functional outcomes at 3 months and 1 year respectively. Reperfusion reduced the risk of worsening (adjusted odds ratio [OR]: 0.24, 95% confidence interval [CI]: 0.12-0.49, P  <0.01), 30-day death (adjusted OR: 0.22, 95% CI: 0.11-0.41, P  <0.01), and unfavorable functional outcomes at 3 months (adjusted OR: 0.24, 95% CI: 0.08-0.68, P <0.01) and 1 year (adjusted OR: 0.17, 95% CI: 0.06-0.50, P  <0.01). CONCLUSIONS: Approximately one-fifth of patients with ischemic stroke had severe neurological deficits on admission. Clinical worsening mainly occurred in the first 3 to 4 days after stroke onset, with brain edema as the leading cause of worsening. Reperfusion reduced the risk of clinical worsening and improved functional outcomes. REGISTRATION ClinicalTrials.gov , NCT03222024.
Humans ; Male ; Female ; Prospective Studies ; Ischemic Stroke/mortality* ; Aged ; Middle Aged ; Aged, 80 and over ; Stroke ; Brain Ischemia

Objective: To establish a novel classification system for predicting the risk of intraoperative neurophysiological monitoring (IONM) events in surgically-treated patients with kyphotic deformity. Methods: Patients with kyphotic deformity who underwent surgical correction of cervicothoracic, thoracic, or thoracolumbar kyphosis in our center from July 2005 to December 2020 were recruited. We proposed a classification system to describe the morphology of the spinal cord on T2-weighted sagittal magnetic resonance imaging: type A, circular/symmetric cord with visible cerebrospinal fluid (CSF) between the cord and vertebral body; type B, circular/oval/symmetric cord with no visible CSF between the cord and vertebral body; type C, spinal cord that is fattened/deformed by the vertebral body, with no visible CSF between the cord and vertebral body. Furthermore, based on type C, the spinal cord compression ratio (CR) < 50% was defined as the subtype C-, while the spinal cord CR ≥ 50% was defined as the subtype C+. IONM event was documented, and a comparative analysis was made to evaluate the prevalence of IONM events among patients with diverse spinal cord types. Results: A total of 294 patients were reviewed, including 73 in type A; 153 in type B; 53 in subtype C- and 15 in subtype C+. Lower extremity transcranial motor-evoked potentials and/or somatosensory evoked potentials were lost intraoperatively in 41 cases (13.9%), among which 4 patients with type C showed no return of spinal cord monitoring data. The 14 subtype C+ patients (93.3%) had IONM events. Univariate logistic regression analysis showed that patients with a type C spinal cord (subtype C-: odds ratio [OR], 10.390; 95% confidence interval [CI], 2.215–48.735; p = 0.003; subtype C+, OR, 497.000; 95% CI, 42.126– 5,863.611; p < 0.001) are at significantly higher risk of a positive IONM event during deformity correction compared to those with a type A. In further multiple logistic regression analysis, the spinal cord classification (OR, 5.371; 95% CI, 2.966–9.727; p < 0.001) was confirmed as an independent risk factor for IONM events. Conclusion We presented a new spinal cord classification system based on the relative position of the spinal cord and vertebrae to predict the risk of IONM events in patients with kyphotic deformity. In patients with type C spinal cord, especially those in C+ cases, it is essential to be aware of potential IONM events, and adopt standard operating procedures to facilitate neurological recovery.

Objective: To establish a novel classification system for predicting the risk of intraoperative neurophysiological monitoring (IONM) events in surgically-treated patients with kyphotic deformity. Methods: Patients with kyphotic deformity who underwent surgical correction of cervicothoracic, thoracic, or thoracolumbar kyphosis in our center from July 2005 to December 2020 were recruited. We proposed a classification system to describe the morphology of the spinal cord on T2-weighted sagittal magnetic resonance imaging: type A, circular/symmetric cord with visible cerebrospinal fluid (CSF) between the cord and vertebral body; type B, circular/oval/symmetric cord with no visible CSF between the cord and vertebral body; type C, spinal cord that is fattened/deformed by the vertebral body, with no visible CSF between the cord and vertebral body. Furthermore, based on type C, the spinal cord compression ratio (CR) < 50% was defined as the subtype C-, while the spinal cord CR ≥ 50% was defined as the subtype C+. IONM event was documented, and a comparative analysis was made to evaluate the prevalence of IONM events among patients with diverse spinal cord types. Results: A total of 294 patients were reviewed, including 73 in type A; 153 in type B; 53 in subtype C- and 15 in subtype C+. Lower extremity transcranial motor-evoked potentials and/or somatosensory evoked potentials were lost intraoperatively in 41 cases (13.9%), among which 4 patients with type C showed no return of spinal cord monitoring data. The 14 subtype C+ patients (93.3%) had IONM events. Univariate logistic regression analysis showed that patients with a type C spinal cord (subtype C-: odds ratio [OR], 10.390; 95% confidence interval [CI], 2.215–48.735; p = 0.003; subtype C+, OR, 497.000; 95% CI, 42.126– 5,863.611; p < 0.001) are at significantly higher risk of a positive IONM event during deformity correction compared to those with a type A. In further multiple logistic regression analysis, the spinal cord classification (OR, 5.371; 95% CI, 2.966–9.727; p < 0.001) was confirmed as an independent risk factor for IONM events. Conclusion We presented a new spinal cord classification system based on the relative position of the spinal cord and vertebrae to predict the risk of IONM events in patients with kyphotic deformity. In patients with type C spinal cord, especially those in C+ cases, it is essential to be aware of potential IONM events, and adopt standard operating procedures to facilitate neurological recovery.

Objective:To explore the predictive value of 18F-FDG PET/CT in molecular subtyping of triple-negative breast cancer. Methods:A retrospective analysis was performed on the clinical and imaging data of 227 breast cancer patients who underwent 18F-FDG PET/CT examination in the Tianjin Medical University Cancer Institute & Hospital from January 1, 2010 to December 31, 2022. Based on the expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) in the primary breast cancer, the patients were categorized into two groups: triple-negative breast cancer (TNBC) and non-TNBC. Radiomic features were extracted from images of both groups, and a radiomic model was constructed to predict the molecular subtype of the TNBC groups. In addition, the clinical data, CT morphological features, and PET metabolic parameters of both groups were compared to determine the indicators with statistically significant differences and develop a comprehensive radiomic model combined with clinical characteristics. Results:Compared to the non-TNBC group, the TNBC groups exhibited more significant invasiveness in terms of tumor diameter, margins, ipsilateral axillary lymph node metastasis, invasion of neighboring skin or papillae, and PET metabolic parameters ( t = -3.19; χ2 = 7.30, 8.10, 5.34; t = 3.80, 3.30, 3.42, P < 0.05). The constructed 18F-FDG PET/CT radiomic model proved effective in predicting the molecular subtype of the TNBC group, and the receiver operating characteristic (ROC) curve showed an area under the curve (AUC) of 0.83 (95% CI 0.78-0.88), an accuracy of 75.9%, a sensitivity of 74.5%, and a specificity of 77.2%. In contrast, the constructed comprehensive radiomic model displayed an AUC of 0.86 (95% CI 0.81-0.90), an accuracy of 77.2%, a sensitivity of 78.6%, and a specificity of 75.9%. Conclusions:18F-FDG PET/CT plays an important role in predicting molecular subtypes of TNBC. The constructed radiomic model and comprehensive radiomic model can further enhance the prediction efficacy of PET metabolic parameters and accelerate the development of accurate treatment protocols in clinical practice, thus improving the prognosis of breast cancer.

Objective:To investigate the effect of Hounsfield Units (HU) at the upper instrumented vertebra (UIV) on postoperative proximal junctional kyphosis (PJK) after pelvic fixation with second sacral alar-iliac (S 2AI) screws in patients with degenerative spinal deformity. Methods:A total of 66 patients with degenerative spinal deformity who underwent pelvic fixation with S 2AI screws from August 2015 to April 2021 were retrospectively reviewed. The cohort included 4 males and 62 females, aged 61.9±7.3 years (range, 43-78 years), with a follow-up period of 18.4±14.3 months (range, 6-60 months). The prevalence of PJK was 26%. Patients were divided into two groups based on the occurrence of PJK during postoperative follow-up: the PJK group (17 cases) and the non-PJK group (49 cases). HU measurements were taken at the UIV, the vertebral body cephalad to the UIV (UIV+1), and the L 3 and L 4 vertebral bodies. The following sagittal radiographic parameters were measured: thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), PI minus LL (PI-LL), and sagittal vertical axis (SVA) at preoperative, postoperative, and final follow-up. General information and HU values of the two groups were compared, and Pearson correlation analysis was performed on HU values, bone mineral density (BMD), and T scores. Logistic regression analysis was used to explore the risk factors for PJK. Results:The HU values of L 3 and L 4 were significantly positively correlated with the BMD and T scores respectively ( r=0.530, P<0.001; r=0.537, P<0.001). Age, gender, follow-up time, fixation levels, bone mineral density (BMD) and T-score were not significantly different between PJK and non-PJK group. The average HU values of UIV and UIV+1 in PJK group was 104.3±32.9, whlie the average HU values of UIV and UIV+1 in non-PJK group was 133.7±29.5. The difference of HU between the two groups was statistically significant ( t=3.441, P=0.001). Logistic regression analysis showed that average HU values of UIV and UIV+1 [ OR=0.960, 95% CI(0.933, 0.987), P=0.004] and changes of lumbar lordosis [ OR=1.049, 95% CI(1.007, 1.092), P=0.023] were independent risk factors for PJK, with an optimal cutoff obtained by ROC that 106 for average HU values of UIV and UIV+1 and 22.5° for changes of LL. Conclusion:The average HU values of UIV and UIV+1 < 106 and changes of lumbar lordosis > 22.5° are independent risk factors for PJK after pelvic fixation with second sacralalar-iliac in patients with degenerative spinal deformity.

Objective To evaluate the differential diagnostic value of synthetic magnetic resonance imaging(syMRI)and field of view optimized and constrained undistorted single shot diffusion weighted imaging(FOCUS DWI)in patient with breast imaging reporting and data system(BI-RADS)4 breast lesions.Methods A total of 68 patients who underwent breast MRI and were classified as BI-RADS category 4 were prospectively enrolled.Among them,there were 31 cases of benign lesions(benign group)and 37 cases of malignant lesions(malignant group).All patients underwent T1WI,T2WI,FOCUS DWI,dynamic contrast-enhanced magnetic resonance ima-ging(DCE-MRI)and syMRI.Two radiologists delineated the region of interest(ROI)on quantitative parameters images of syMRI and the apparent diffusion coefficient(ADC)images generated from FOCUS DWI and calculated T1,T2,proton density(PD)and ADC values,respectively.The thresholds and diagnostic efficacy of syMRI and FOCUS DWI parameters were evaluated by the receiver op-erating characteristic(ROC)curve.Logistic regression analysis was used to combine the parameters of the two sequences and evalu-ate the diagnostic efficacy.Results The T2,PD,and ADC values in the malignant group were significantly lower than those in the benign group(P＜0.05),but there were no statistically significant difference in T1 values between the groups(P＞0.05).T2 and ADC values could be used as important diagnostic indexes in patient with malignant lesions of BI-RADS 4 breast lesions,and the area under the curve(AUC)of T2 and ADC was 0.833 and 0.867,respec-tively.There was no significant difference in AUC of T2 and ADC between benign and malignant groups(Z=0.485,P=0.627).The AUC of T2 value combined with ADC value was 0.910,and the sensitivity and specificity was 90.3％and 89.2％,respectively.Conclusion T2 value of syMRI and ADC value of FOCUS DWI can be used as quantitative diagnostic indicators in patients with BI-RADS 4 breast lesions.The combination of T2 and ADC values can further improve the differential diagnosis efficiency.

Objective To compare artificial intelligence-assisted diagnostic system and conventional manual CT image interpretation for detection of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules, and to provide a reference for the application of artificial intelligence in clinical screening for lung cancer. Methods Patients who underwent chest CT scans for pulmonary nodules from March 2019 to December 2023 were enrolled. The CT images were subjected to artificial intelligence-based and conventional manual CT image interpretation. The pathological examination results of pulmonary lesions served as a gold standard for comparison of artificial intelligence-based and conventional manual CT image interpretation in detection rate of positive pulmonary nodules and differential diagnosis of benign and malignant pulmonary nodules. Results A total of 327 positive pulmonary nodules were identified in 207 patients. The detection rate of positive pulmonary nodules was significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation (95.72% vs. 86.85%; χ²=16.16, P < 0.01). Moreover, artificial intelligence-based CT image interpretation showed significantly higher detection rates for solid (χ²=7.71, P < 0.01) and ground-glass pulmonary nodules (χ²=5.80, P < 0.05) than conventional manual CT image interpretation. The detection rates for pulmonary nodules with < 1 cm (χ²=4.97, P < 0.05), 1 to < 2 cm (χ²=7.04, P < 0.01), and 2 to < 3 cm (χ²=4.91, P < 0.05) diameters were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for differential diagnosis of benign and malignant pulmonary nodules were 98.08%, 91.53%, 95.33%, 96.43%, and 95.71% with artificial intelligence-based CT image interpretation and 91.34%, 77.97%, 87.96%, 32.62%, and 86.50% with conventional CT image interpretation. The sensitivity (χ²=4.70, P < 0.05), specificity (χ²=4.20, P < 0.05), negative predictive value (χ²=65.28, P < 0.01), and accuracy (χ²=8.52, P < 0.01) were significantly higher with artificial intelligence-based CT image interpretation than with conventional manual CT image interpretation. However, there was no significant difference in the positive predictive value (χ²=3.80, P > 0.05). Conclusion Compared with conventional manual CT image interpretation, artificial intelligence-assisted diagnostic system for CT image interpretation can significantly increase the detection rate of positive pulmonary nodules and improve the efficiency of differential diagnosis of benign and malignant pulmonary nodules, so it deserves widespread applications in physical examination and early screening for lung cancer.