AIMC Topic: Neoplasm Staging
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Robot-assisted retroperitoneal lymph node dissection: Initial experience in Japan.
Asian journal of endoscopic surgery
Nov 9, 2023
For patients with testicular tumors who need the surgical management, open retroperitoneal lymph node dissection (O-RPLND) is considered the gold standard treatment. However, recently, robot-assisted RPLND (R-RPLND) has gained popularity as a minimal...
A contemporary analysis of disease upstaging of Gleason 3 + 3 prostate cancer patients after robot-assisted laparoscopic prostatectomy.
Cancer medicine
Nov 6, 2023
BACKGROUND: Risk of biochemical recurrence (BCR) in localised prostate cancer can be stratified using the 5-tier Cambridge Prognostic Group (CPG) or 3-tier European Association of Urology (EAU) model. Active surveillance is the current recommendation...
Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning.
Surgery today
Oct 20, 2023
PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.
Initial experience with the da Vinci SP robot-assisted surgical staging of endometrial cancer: a retrospective comparison with conventional laparotomy.
Journal of robotic surgery
Oct 10, 2023
To compare the perioperative outcomes of surgical staging performed using conventional laparotomy (LT) or the da Vinci SP robotic system (SP) in patients with endometrial cancer. We retrospectively analyzed 180 patients with stage I-III endometrial c...
Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.
Journal of medical imaging and radiation oncology
Sep 19, 2023
INTRODUCTION: Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately diagnose on preoperative imaging. This study aimed to develop and evaluate a deep learning model to pr...
Robot-assisted fluorescent sentinel lymph node identification in early-stage colon cancer.
Surgical endoscopy
Sep 18, 2023
BACKGROUND: Patients with cT1-2 colon cancer (CC) have a 10-20% risk of lymph node metastases. Sentinel lymph node identification (SLNi) could improve staging and reduce morbidity in future organ-preserving CC surgery. This pilot study aimed to asses...
The Fidelity of Artificial Intelligence to Multidisciplinary Tumor Board Recommendations for Patients with Gastric Cancer: A Retrospective Study.
Journal of gastrointestinal cancer
Sep 13, 2023
PURPOSE: Due to significant growth in the volume of information produced by cancer research, staying abreast of recent developments has become a challenging task. Artificial intelligence (AI) can learn, reason, and understand the enormous corpus of l...
Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.
Medical physics
Aug 13, 2023
BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and t...
Enhancing the prediction of IDC breast cancer staging from gene expression profiles using hybrid feature selection methods and deep learning architecture.
Medical & biological engineering & computing
Aug 2, 2023
Prediction of the stage of cancer plays an important role in planning the course of treatment and has been largely reliant on imaging tools which do not capture molecular events that cause cancer progression. Gene-expression data-based analyses are a...
Automated localization and segmentation of cervical lymph nodes on contrast-enhanced CT using a 3D foveal fully convolutional neural network.
European radiology experimental
Jul 28, 2023
BACKGROUND: In the management of cancer patients, determination of TNM status is essential for treatment decision-making and therefore closely linked to clinical outcome and survival. Here, we developed a tool for automatic three-dimensional (3D) loc...
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