Pre-operative

For patients with locally advanced rectal cancer (LARC), total neoadjuvant therapy (TNT), namely, intensifying preoperative treatment through the integration of radiotherapy and systemic chemotherapy before surgery, was commonly recommended as the standard treatment.

10p vishanshan 27-06-2024 1 1   Download

Based on the quantitative and qualitative features of CT imaging, a model for predicting the invasiveness of ground-glass nodules (GGNs) was constructed, which could provide a reference value for preoperative planning of GGN patients.

12p vishanshan 27-06-2024 1 1   Download

CRC with liver metastases is a major contributor to cancer-related mortality. Despite advancements in liver resection techniques, patient survival remains a concern due to high recurrence rates. This study seeks to uncover prognostic biomarkers that predict overall survival in patients undergoing curative hepatic resection for CRC liver metastases.

9p vishanshan 27-06-2024 3 1   Download

Periampullary cancers, including pancreatic ductal adenocarcinoma, ampullary-, cholangio, and duodenal carcinoma, are frequently diagnosed in an advanced stage and are associated with poor overall survival.

12p vishanshan 27-06-2024 1 1   Download

Postoperative central diabetes insipidus (CDI) is commonly observed in craniopharyngioma (CP) patients, and the inflammatory response plays an important role in CPs. We aimed to evaluate the predictive value of preoperative peripheral inflammatory markers and their combinations regarding CDI occurrence in CPs.

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The index composed of preoperative lymphocytes, albumin, and neutrophils (LANR), a new composite score based on inflammatory response and nutritional status, has been reported to be associated with the prognosis of multiple types of cancer, but the role of LANR in the prognosis of resectable pancreatic ductal adenocarcinoma (PDAC) has not yet been elucidated.

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To compare the diagnostic performance of the Node-RADS scoring system and lymph node (LN) size in preoperative LN assessment for rectal cancer (RC), and to investigate whether the selection of size as the primary criterion whereas morphology as the secondary criterion for LNs can be considered the preferred method for clinical assessment.

13p vikoch 27-06-2024 1 1   Download

Using the preoperative pan-immune-inflammation value (PIV) and the monocyte to high-density lipoprotein ratio (MHR) to reflect inflammation, immunity, and cholesterol metabolism, we aim to develop and visualize a novel nomogram model for predicting the survival outcomes in patients with colorectal cancer (CRC).

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Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated with radical cystectomy (RC).

12p vikoch 27-06-2024 2 1   Download

An accurate and non-invasive approach is urgently needed to distinguish tuberculosis granulomas from lung adenocarcinomas. This study aimed to develop and validate a nomogram based on contrast enhancedcompute tomography (CE-CT) to preoperatively differentiate tuberculosis granuloma from lung adenocarcinoma appearing as solitary pulmonary solid nodules (SPSN).

13p vikoch 27-06-2024 1 1   Download

Although radical surgical resection is the most effective treatment for hepatocellular carcinoma (HCC), the high rate of postoperative recurrence remains a major challenge, especially in patients with alpha-fetoprotein (AFP)-negative HCC who lack effective biomarkers for postoperative recurrence surveillance. In this study, we propose to develop a radiomics model based on preoperative CECT to predict the risk of early recurrence after surgery in AFP-negative HCC.

12p vikoch 27-06-2024 1 1   Download

This study aims to develop an innovative, deep model for thymoma risk stratification using preoperative CT images. Current algorithms predominantly focus on radiomic features or 2D deep features and require manual tumor segmentation by radiologists, limiting their practical applicability.

9p vikoch 27-06-2024 2 1   Download

Preoperative prediction of International Federation of Gynecology and Obstetrics (FIGO) stage in patients with epithelial ovarian cancer (EOC) is crucial for determining appropriate treatment strategy. This study aimed to explore the value of contrast-enhanced CT (CECT) radiomics in predicting preoperative FIGO staging of EOC, and to validate the stability of the model through an independent external dataset.

11p vikoch 27-06-2024 1 1   Download

Preoperative diagnosis of flum terminale ependymomas (FTEs) versus schwannomas is difficult but essential for surgical planning and prognostic assessment. With the advancement of deep-learning approaches based on convolutional neural networks (CNNs), the aim of this study was to determine whether CNN-based interpretation of magnetic resonance (MR) images of these two tumours could be achieved.

11p vikoch 27-06-2024 1 1   Download

This study aimed to develop and validate a machine learning (ML)-based fusion model to preoperatively predict Ki-67 expression levels in patients with head and neck squamous cell carcinoma (HNSCC) using multiparametric magnetic resonance imaging (MRI).

14p vikoch 27-06-2024 3 1   Download

To explore the association between preoperative WBC count and the long-term survival outcomes and clinical outcomes in different stage patients who underwent surgical resection for colorectal cancer (CRC).

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Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features.

12p vikoch 27-06-2024 2 1   Download

The low specificity of Thyroid Imaging Reporting and Data System (TI-RADS) for preoperative benignmalignant diagnosis leads to a large number of unnecessary biopsies. This study developed and validated a predictive model based on MRI morphological features to improve the specificity.

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Glioma recurrence, subsequent to maximal safe resection, remains a pivotal challenge. This study aimed to identify key clinical predictors influencing recurrence and develop predictive models to enhance neurological diagnostics and therapeutic strategies.

12p vikoch 27-06-2024 1 1   Download

The risk category of gastric gastrointestinal stromal tumors (GISTs) are closely related to the surgical method, the scope of resection, and the need for preoperative chemotherapy. We aimed to develop and validate convolutional neural network (CNN) models based on preoperative venous-phase CT images to predict the risk category of gastric GISTs.

10p vikoch 27-06-2024 2 1   Download