Enhanced MRI Radiomics Based Model for Predicting Recurrence or Metastasis of Nasopharyngeal Cancer (NC) Undergoing Concurrent Chemoradiotherapy: A Retrospective Study.

Nasopharyngeal Carcinoma (NC) refers to the malignant tumor that occurs at the top and side walls of the nasopharyngeal cavity. The NC incidence rate always dominates the first among the malignant tumors of the ear, nose and throat, and mainly occurs in Asia. NC cases are mainly concentrated in southern provinces in China, with about 4 million existing NC. With the pollution of environment and pickled diet, and the increase of life pressure, the domestic NC incidence rate has reached 4.5-6.5/100000 and is increasing year by year. It was reported that the known main causes of NC include hereditary factor, genetic mutations, and EB virus infection, common clinical symptoms of NC include nasal congestion, bloody mucus, etc. About 90% of NC is highly sensitive to radiotherapy which is regard as the preferred treatment method; However, for NC with lower differentiation, larger volume, and recurrence after treatment, surgical resection and local protons and heavy ions therapy are also indispensable means. According to reports, the subtle heterogeneity and diversity exists in some NC, with about 80% of NC undergone radiotherapy and about 25% experienced recurrence and death within five years after radiotherapy in China. Therefore, screening the NC population with suspected recurrence after concurrent chemoradiotherapy may improve survival rates in current clinical decision-making.

NC is one of the prevalent malignancies of the head and neck region with poor prognosis. The aim of this study is to establish a predictive model for assessing NC prognosis using clinical and MR radiomics data.

Prediction of High-Risk Gastrointestinal Stromal Tumor Recurrence Based on Delta-CT Radiomics Modeling: A 3-Year Follow-up Study After Surgery.

Background: Medium- to high-risk classification-gastrointestinal stromal tumors (MH-GIST) have a high recurrence rate and are difficult to treat. This study aims to predict the recurrence of MH-GIST within 3 years after surgery based on clinical data and preoperative Delta-CT Radiomics modeling. Methods: A retrospective analysis was conducted on clinical imaging data of 242 cases confirmed to have MH-GIST after surgery, including 92 cases of recurrence and 150 cases of normal. The training set and test set were established using a 7:3 ratio and time cutoff point. In the training set, multiple prediction models were established based on clinical data of MH-GIST and the changes in radiomics texture of enhanced computed tomography (CT) at different time periods (Delta-CT radiomics). The area under curve (AUC) values of each model were compared using the Delong test, and the clinical net benefit of the model was tested using decision curve analysis (DCA). Then, the model was externally validated in the test set, and a novel nomogram predicting the recurrence of MH-GIST was finally created. Results: Univariate analysis confirmed that tumor volume, tumor location, neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), diabetes, spicy hot pot, CT enhancement mode, and Radscore 1/2 were predictive factors for MH-GIST recurrence (P < .05). The combined model based on these above factors had significantly higher predictive performance (AUC = 0.895, 95% confidence interval [CI] = [0.839-0.937]) than the clinical data model (AUC = 0.735, 95% CI = [0.6 62-0.800]) and radiomics model (AUC = 0.842, 95% CI = [0.779-0.894]). Decision curve analysis also confirmed the higher clinical net benefit of the combined model, and the same results were validated in the test set. The novel nomogram developed based on the combined model helps predict the recurrence of MH-GIST. Conclusions: The nomogram of clinical and Delta-CT radiomics has important clinical value in predicting the recurrence of MH-GIST, providing reliable data reference for its diagnosis, treatment, and clinical decision-making.

Postoperative clinical outcomes with and without short-term intravenous tranexamic acid after posterior lumbar interbody fusion: A prospective cohort study.

The use of tranexamic acid (TXA) in posterior lumbar interbody fusion (PLIF) surgery is believed to be beneficial for reducing intraoperative blood loss, postoperative drainage volume (PDV), and length of hospital stay (LOS). However, whether continued administration of intravenous TXA within 24 hours after surgery is more beneficial to patients has not yet been studied. This study prospectively analyzed the perioperative outcomes of patients who received and did not receive intravenous TXA within 24 hours after PLIF (≥2 segments) surgery from January 2018 to December 2021. A total of 78 and 69 patients were included in the TXA (receive intravenous TXA intraoperatively and within 24 hours postoperatively) and non-TXA (only receive intravenous TXA intraoperatively) groups, respectively. No significant differences were observed in the intraoperative blood loss and operative time between the 2 groups. The postoperative drainage volume, postoperative drainage time, and length of hospital stay in the TXA group were significantly lower than those in the non-TXA group. The rates and volumes of postoperative blood and albumin transfusions were significantly lower in the TXA group than those in the non-TXA group. No significant differences were observed in the perioperative complication rates between the 2 groups. No increase in thrombosis-related complications was observed with postoperative TXA administration. Short-term TXA use after PLIF (≥2 segments) surgery is safe. In addition to intraoperative use of TXA, additionally administration of intravenous TXA within 24 hours postoperatively can improve the perioperative clinical outcomes of patients without increasing the risk of thrombotic events.

Risk factor of residual leg numbness after lumbar microdiscectomy for lumbar disc herniation.

Although patients with lumbar disc herniation (LDH) can achieve significant relief from lower back and leg pain after lumbar microdiscectomy, a few patients complain of discomfort due to residual leg numbness (RLN). This study aimed to identify potential risk factors for RLN after lumbar microdiscectomy. We prospectively collected and analyzed patients with LDH who underwent microdiscectomy between September 2016 and December 2020. All included patients had preoperative LN symptoms. Patients with RLN were defined as those with LN at the last follow-up. The relationships between RLN and sex, age, body mass index (BMI), current smoking status, diabetes mellitus, revision surgery, preoperative LN Numeric Rating Scale (NRS) score, duration of preoperative LN, RLN at discharge, sagittal range of motion (SROM), Modic change, disc Pfirrmann grade were analyzed. The RLN was observed in 33.5% (112/334) of patients at the last follow-up. No significant differences were observed in age, sex, BMI, current smoking status, or diabetes between the RLN and non-RLN groups. The preoperative LN NRS score, preoperative LN duration, rate of RLN at discharge, and revision surgery were significantly higher in the RLN group than those in the non-RLN group. Multivariate logistic regression analysis identified the preoperative LN NRS score, duration of preoperative LN, RLN at discharge, revision surgery, and SROM as risk factors for RLN in the long-term follow-up. Patients with higher preoperative LN NRS scores and SROM, longer preoperative LN duration, RLN at discharge, and revision surgery were more likely to experience RNL after lumbar microdiscectomy.

Analysis of the Relationship Between Modic Change and Spinopelvic Parameters in the Sagittal Plane.

BACKGROUND This study explored relationship between Modic change and spinopelvic parameters in the sagittal plane. MATERIAL AND METHODS We divided 80 patients into 4 groups: 60 subjects diagnosed with Modic changes (MC) were enrolled in the MC groups (MC1, MC2, and MC3) with each MC type consisting of 20 subjects, and 60 healthy subjects were enrolled in the control group. Spinopelvic parameters in the sagittal plane were calculated to assess their associations with MC. Multivariate logistic regression was used to explore possible risk factors for MC. RESULTS PI and LL in the MC groups were significant smaller than in the control group (p<0.05). PI, SS, and PT were significantly correlated with LL with a correlation coefficient of 0.75PI, 0.71SS and 0.69PT (p<0.05). Multivariate logistic regression of the significant variables showed that PI (less than 43.2°) is an independent significant risk factor for MC. ROC analysis showed that moderate diagnostic value was obtained for the significant variable, with an area under the curve (AUC) of 0.80 (p>0.05). CONCLUSIONS We concluded that PI is risk factor for MC, and smaller PI is associated with higher incidence of MC.