AIMC Topic: Neoadjuvant Therapy
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Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework.
BMC cancer
Mar 7, 2024
PURPOSE: Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed...
The role of neoadjuvant chemotherapy for patients with variant histology muscle invasive bladder cancer undergoing robotic cystectomy: Data from the International Robotic Cystectomy Consortium.
Urologic oncology
Feb 29, 2024
OBJECTIVE: To assess the role of neoadjuvant chemotherapy (NAC) before robot-assisted radical cystectomy (RARC) for patients with variant histology (VH) muscle-invasive bladder cancer (MIBC).
Fusion Radiomics-Based Prediction of Response to Neoadjuvant Chemotherapy for Osteosarcoma.
Academic radiology
Dec 27, 2023
RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is the most crucial prognostic factor for osteosarcoma (OS), it significantly prolongs progression-free survival and improves the quality of life. This study aims to develop a deep learning rad...
Neoadjuvant Therapy
Contrast Media
Magnetic Resonance Imaging
Child
Nomograms
Treatment Outcome
Chemotherapy, Adjuvant
Osteosarcoma
Bone Neoplasms
Predictive Value of Tests
Sensitivity and Specificity
Radiomics
Male
Middle Aged
Deep Learning
Adolescent
Female
Young Adult
Adult
Humans
Retrospective Studies
Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Dec 7, 2023
INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision o...
Diagnostic accuracy of radiomics-based machine learning for neoadjuvant chemotherapy response and survival prediction in gastric cancer patients: A systematic review and meta-analysis.
European journal of radiology
Dec 5, 2023
BACKGROUND: In recent years, researchers have explored the use of radiomics to predict neoadjuvant chemotherapy outcomes in gastric cancer (GC). Yet, a lingering debate persists regarding the accuracy of these predictions. Against this backdrop, this...
PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.
Breast cancer research : BCR
Nov 13, 2023
BACKGROUND: Invasive breast cancer patients are increasingly being treated with neoadjuvant chemotherapy; however, only a fraction of the patients respond to it completely. To prevent overtreatment, there is an urgent need for biomarkers to predict t...
ASO Author Reflections: Deep-Learning Radiomics Nomogram Based on Enhanced CT to Predict the Effect of Neoadjuvant Chemotherapy on Metastatic Lymph Nodes in Locally Advanced Gastric Cancer.
Annals of surgical oncology
Nov 6, 2023
Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer.
Annals of surgical oncology
Nov 5, 2023
BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant c...
Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.
Academic radiology
Oct 31, 2023
RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary response after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients.
Towards deep-learning (DL) based fully automated target delineation for rectal cancer neoadjuvant radiotherapy using a divide-and-conquer strategy: a study with multicenter blind and randomized validation.
Radiation oncology (London, England)
Oct 6, 2023
PURPOSE: Manual clinical target volume (CTV) and gross tumor volume (GTV) delineation for rectal cancer neoadjuvant radiotherapy is pivotal but labor-intensive. This study aims to propose a deep learning (DL)-based workflow towards fully automated cl...
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