Development and validation of a machine learning-based F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival.

Background: Survival prognosis of patients with gastric cancer (GC) often influences physicians' choice of their follow-up treatment. This study aimed to develop a positron emission tomography (PET)-based radiomics model combined with clinical tumor-node-metastasis (TNM) staging to predict overall survival (OS) in patients with GC.

Methods: We reviewed the clinical information of a total of 327 patients with pathological confirmation of GC undergoing 18 F-fluorodeoxyglucose (18 F-FDG) PET scans.

Radiomics based on machine learning algorithms could predict prognosis and postoperative chemotherapy benefits of patients with gastric cancer: a retrospective cohort study.

Background: Traditional clinical characteristics have certain limitations in evaluating cancer prognosis. The radiomics features provide information on tumor morphology, tissue texture, and hemodynamics, which can accurately reflect personalized predictions. This study investigated the clinical value of radiomics features on contrast-enhanced computed tomography (CT) images in predicting prognosis and postoperative chemotherapy benefits for patients with gastric cancer (GC).

NSUN2 Promotes Tumor Progression and Regulates Immune Infiltration in Nasopharyngeal Carcinoma.

Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in the head and neck with a complex etiology, such as environmental factors, genetic factors, and Epstein-Barr virus infection. The NOP2/Sun domain family, member 2 (NSUN2) is a methyltransferase of m5C methylation modification that has been reported to be involved in the occurrence and progression of various tumors, but its role in NPC remains unclear. In this study, we found that NSUN2 was upregulated in NPC and predicted a poor prognosis for NPC patients in both GEO datasets and our tissue microarrays containing 125 NPC tissues.

White matter alterations in heart-kidney imbalance insomnia and Jiao-Tai-Wan treatment: A diffusion-tensor imaging study.

Previous studies have reported changes in white matter microstructures in patients with insomnia. However, few neuroimaging studies have focused specifically on white matter tracts in insomnia patients after having received treatment. In this prospective study, diffusion-tensor imaging was used in two samples of heart-kidney imbalance insomnia patients who were treated with placebo or Jiao-Tai-Wan, a traditional Chinese medicine commonly used to treat heart-kidney imbalance insomnia, to assess the changes in white matter tracts.

Dilated Optic Nerve Sheath Diameter Predicts Poor Outcome in Acute Spontaneous Intracerebral Hemorrhage.

Background And Purpose: Optic nerve sheath diameter (ONSD) enlargement occurs in patients with intracerebral hemorrhage (ICH). However, the relationship between ONSD and prognosis of ICH is uncertain. This study aimed to investigate the predictive value of ONSD on poor outcome of patients with acute spontaneous ICH.

Radiomics for intracerebral hemorrhage: are all small hematomas benign?

Objectives: We hypothesized that not all small hematomas are benign and that radiomics could predict hematoma expansion (HE) and short-term outcomes in small hematomas.

Methods: We analyzed 313 patients with small (<10 ml) intracerebral hemorrhage (ICH) who underwent baseline non-contrast CT within 6 h of symptom onset between September 2013 and February 2019. Poor outcome was defined as a Glasgow Outcome Scale score ≤3.

Prediction of Clinical Outcome at Discharge After Rupture of Anterior Communicating Artery Aneurysm Using the Random Forest Technique.

Aneurysmal subarachnoid hemorrhage (SAH) is a devastating disease. Anterior communicating artery (ACoA) aneurysm is the most frequent location of intracranial aneurysms. The purpose of this study is to predict the clinical outcome at discharge after rupture of ACoA aneurysms using the random forest machine learning technique.

Brain-Region Specific Metabolic Abnormalities in Parkinson's Disease and Levodopa-Induced Dyskinesia.

Several lines of evidence point to alteration in brain metabolic homeostasis in Parkinson's disease (PD) and levodopa-induced dyskinesia (LID), yet the metabolic mechanism in different brain regions underlying PD and LID remains largely unknown. The present study aimed to uncover the metabolic pathways across anatomical regions in the brain of PD and LID. Using an NMR-based metabolomic approach, we generated the metabolomics profiling data from six different brain regions of PD rats and following the onset of LIDs.

Clinical-radiomics Nomogram for Risk Estimation of Early Hematoma Expansion after Acute Intracerebral Hemorrhage.

Rationale And Objectives: Noncontrast CT-based radiomics signature has shown ability for detecting hematoma expansion (HE) in spontaneous intracerebral hemorrhage (ICH). We sought to compare its predictive performance with clinical risk factors and develop a clinical-radiomics nomogram to assess the risk of early HE.

Materials And Methods: In total, 1153 patients with ICH who underwent baseline cranial CT within 6 hours and follow-up scans within 72 hours of stroke onset were enrolled, of whom 864 (75%) were assigned to the derivation cohort and 289 (25%) to the validation cohort.

Association Between Eosinophilic Leukocyte Count and Hematoma Expansion in Acute Spontaneous Intracerebral Hemorrhage.

Hematoma expansion (HE) predicts poor outcome and is an appealing treatment target in spontaneous intracerebral hemorrhage (ICH). Clinical evidence has shown an association of HE with peripheral white blood cells (WBC) count, but the individual contributions of leukocyte subtypes between literatures are described inconsistently. Our aim was to determine the relationship between admission absolute and differential leukocyte counts and HE by using different growth definitions.

Comparison of Ultra-Early Hematoma Growth and Common Noncontrast Computed Tomography Features in Predicting Hematoma Enlargement in Patients with Spontaneous Intracerebral Hemorrhage.

Objective: Ultra-early hematoma growth (uHG), the black hole sign, and the blend sign are common predictors of hematoma enlargement (HE). This study aimed to develop a new diagnostic criterion for predicting HE using uHG and to compare the accuracy of uHG, the black hole sign, and the blend sign in predicting HE in patients with spontaneous intracerebral hemorrhage (sICH).

Methods: We retrospectively analyzed data of 920 patients with sICH from August 2013 to January 2018.