AIMC Topic: Pathologic Complete Response

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Non-invasive CT based multiregional radiomics for predicting pathologic complete response to preoperative neoadjuvant chemoimmunotherapy in non-small cell lung cancer.

European journal of radiology May 19, 2025
PURPOSE: This study aims to develop and validate a multiregional radiomics model to predict pathological complete response (pCR) to neoadjuvant chemoimmunotherapy in non-small cell lung cancer (NSCLC), and further evaluate the performance of the mode...
Reproducibility of Results Aged Adult Radiomics Retrospective Studies Tomography, X-Ray Computed Female Treatment Outcome Neoadjuvant Therapy Carcinoma, Non-Small-Cell Lung Pathologic Complete Response Male Middle Aged Lung Neoplasms Immunotherapy Humans
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Detection of pathologic complete response using deep neural network-based endoscopic evaluation in patients with esophageal cancer receiving neoadjuvant chemotherapy: a nationwide multicenter retrospective study from 46 Japanese esophageal centers.

Esophagus : official journal of the Japan Esophageal Society Apr 28, 2025
BACKGROUND: Detecting pathological complete response (pCR) preoperatively facilitated a non-surgical approach after neoadjuvant chemotherapy (NAC). We previously developed a deep neural network-based endoscopic evaluation to determine pCR preoperativ...
Male Middle Aged Humans Deep Learning Neural Networks, Computer Female Retrospective Studies Esophageal Squamous Cell Carcinoma Treatment Outcome Aged Chemotherapy, Adjuvant Neoadjuvant Therapy Sensitivity and Specificity Esophagoscopy Predictive Value of Tests Pathologic Complete Response Esophageal Neoplasms Japan
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Development and validation of an interpretable machine learning model for diagnosing pathologic complete response in breast cancer.

Computer methods and programs in biomedicine Apr 23, 2025
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...
ROC Curve Neoadjuvant Therapy Female Magnetic Resonance Imaging Reproducibility of Results Humans Pathologic Complete Response Breast Neoplasms Machine Learning Middle Aged Algorithms
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Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy.

Journal for immunotherapy of cancer Mar 15, 2025
BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develo...
Immunotherapy Treatment Outcome Neoadjuvant Therapy Esophageal Neoplasms Esophageal Squamous Cell Carcinoma Pathologic Complete Response Radiomics Male Middle Aged Deep Learning Tomography, X-Ray Computed Female Aged Humans Prognosis Retrospective Studies
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Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

JCO clinical cancer informatics Nov 22, 2024
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...
Neoadjuvant Therapy Singapore Chemotherapy, Adjuvant Pathologic Complete Response Breast Neoplasms Middle Aged Antineoplastic Combined Chemotherapy Protocols Treatment Outcome Humans Female Machine Learning Aged Prognosis Adult
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Prediction and validation of pathologic complete response for locally advanced rectal cancer under neoadjuvant chemoradiotherapy based on a novel predictor using interpretable machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Oct 6, 2024
BACKGROUND: Precise evaluation of pathological complete response (pCR) is essential for determining the prognosis of patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy (NCRT) and can offer clues for the selec...
Neoadjuvant Therapy Neoplasm Staging Rectal Neoplasms Chemoradiotherapy Humans Adult Pathologic Complete Response Retrospective Studies Machine Learning Male Female Prognosis Middle Aged Aged ROC Curve
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Comparison of radiomics-based machine-learning classifiers for the pretreatment prediction of pathologic complete response to neoadjuvant therapy in breast cancer.

PeerJ Jul 15, 2024
BACKGROUND: Machine learning classifiers are increasingly used to create predictive models for pathological complete response (pCR) in breast cancer after neoadjuvant therapy (NAT). Few studies have compared the effectiveness of different ML classifi...
Pathologic Complete Response Radiomics Treatment Outcome Humans Middle Aged Female Machine Learning Neoadjuvant Therapy ROC Curve Aged Support Vector Machine Retrospective Studies Adult Magnetic Resonance Imaging Breast Neoplasms
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Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Frontiers in immunology Mar 25, 2024
Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung cancer (NSCLC), and identifying candidates likely responding to this advanced treatment is of important clinical significance. The current multi-instit...
Tomography, X-Ray Computed Tumor Microenvironment Deep Learning Lung Neoplasms Pathologic Complete Response Humans Immunotherapy Retrospective Studies Neoadjuvant Therapy Carcinoma, Non-Small-Cell Lung
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