Radiomics-Driven Imaging Biomarkers for Predicting Chemoradiotherapy Response in Locally Advanced Rectal Cancer

Integrated model of MRI biomarkers and clinical factors for predicting pathologic response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Efficacy of HALP combined with T2-weighted MRI radiomics in predicting pathological complete response and overall survival in rectal cancer after neoadjuvant chemoradiotherapy

This study aimed to develop and validate an integrated model combining pretreatment hemoglobin, albumin, lymphocyte, platelet (HALP) score and T2-weighted magnetic resonance imaging radiomics for predicting pathological complete response (pCR) and overall survival in patients with locally advanced rectal cancer (LARC)...

Pretreatment CT radiomics for prediction of pathological complete response after neoadjuvant chemoimmunotherapy in NSCLC: a multicenter study incorporating habitat analysis

Background Pathological complete response (pCR) after neoadjuvant chemoimmunotherapy (NACI) varies among patients with non-small cell lung cancer (NSCLC). This study aimed to quantify intratumoral heterogeneity using habitat analysis and to develop a pretreatment model for predicting pCR. Methods In this retrospective...

A cfDNA fragmentomics-based machine learning model for predicting treatment response and recurrence in locally advanced rectal cancer after neoadjuvant chemoradiotherapy

Neoadjuvant chemoradiotherapy (nCRT) is standard treatment for locally advanced rectal cancer (LARC), but responses vary substantially. We developed Fragmentia-AI Response, a machine learning model that uses cell-free DNA (cfDNA) fragment features to predict pathological response and recurrence risk without relying on...

A multimodal deep learning radiomics nomogram integrating clinicopathological features for predicting pathological complete response after neoadjuvant therapy in triple-negative breast cancer: a multicenter retrospective study

Among the few multicenter TNBC studies combining MRI, ultrasound, intratumoral/peritumoral radiomics, and attention-based deep learning, this nomogram showed good retrospective accuracy for pCR prediction after NAT and is presented as an aid for pCR prediction and preoperative stratification rather than as direct suppo...

Impact of Tumor Size on Neoadjuvant Chemotherapy Outcomes in Breast Cancer