AIMC Topic: Neoadjuvant Therapy

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RCMIX model based on pre-treatment MRI imaging predicts T-downstage in MRI-cT4 stage rectal cancer.

Cancer letters
Neoadjuvant therapy (NAT) is the standard treatment strategy for MRI-defined cT4 rectal cancer. Predicting tumor regression can guide the resection plane to some extent. Here, we covered pre-treatment MRI imaging of 363 cT4 rectal cancer patients rec...

Artificial intelligence in muscle-invasive bladder cancer: opportunities, challenges, and clinical impact.

Current opinion in urology
PURPOSE OF REVIEW: Muscle-invasive bladder cancer (MIBC) represents an aggressive malignancy with significant morbidity and mortality. Recent advances in artificial intelligence (AI) offer promising opportunities to enhance patient care across the en...

Cone-beam computed tomography-based online adaptive radiotherapy of esophageal cancer in the neoadjuvant setting: Dosimetric analysis, toxicity and treatment response.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Chemoradiotherapy (CRT) followed by surgery is a treatment option for esophageal cancer (EC). However, concerns persist regarding cardiopulmonary toxicity and inconsistent daily target coverage due to anatomical changes. To ad...

Multi-Organ metabolic profiling with [F]F-FDG PET/CT predicts pathological response to neoadjuvant immunochemotherapy in resectable NSCLC.

European journal of nuclear medicine and molecular imaging
PURPOSE: To develop and validate a novel nomogram combining multi-organ PET metabolic metrics for major pathological response (MPR) prediction in resectable non-small cell lung cancer (rNSCLC) patients receiving neoadjuvant immunochemotherapy.

NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.

Journal for immunotherapy of cancer
BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy remains a critical unmet need in resectable non-small-cell lung cancer (NSCLC). Conventional size-base...

Development and validation of an interpretable machine learning model for diagnosing pathologic complete response in breast cancer.

Computer methods and programs in biomedicine
BACKGROUND: Pathologic complete response (pCR) following neoadjuvant chemotherapy (NACT) is a critical prognostic marker for patients with breast cancer, potentially allowing surgery omission. However, noninvasive and accurate pCR diagnosis remains a...

Histological tumor necrosis predicts decreased survival after neoadjuvant chemotherapy in head and neck squamous cell carcinoma.

Oral oncology
OBJECTIVE: Despite growing interest in neoadjuvant therapies, there are no methods to predict radio- (RT) or chemoradiotherapy (CRT) response in head and neck squamous cell carcinoma (HNSCC). The aim of this research was to study the effect of neoadj...