Radiomics, deep learning and early diagnosis in oncology

P Wei - Emerging topics in life sciences, 2021 - portlandpress.com
Medical imaging, including X-ray, computed tomography (CT), and magnetic resonance
imaging (MRI), plays a critical role in early detection, diagnosis, and treatment response …

MRI-based digital models forecast patient-specific treatment responses to neoadjuvant chemotherapy in triple-negative breast cancer

C Wu, AM Jarrett, Z Zhou, N Elshafeey, BE Adrada… - Cancer research, 2022 - AACR
Triple-negative breast cancer (TNBC) is persistently refractory to therapy, and methods to
improve targeting and evaluation of responses to therapy in this disease are needed. Here …

MRI breast: current imaging trends, clinical applications, and future research directions

K Rahmat, NA Mumin, MTR Hamid… - Current Medical …, 2022 - ingentaconnect.com
Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique
in diagnosing breast cancer and is essential in improving cancer detection, lesion …

Four‐dimensional machine learning radiomics for the pretreatment assessment of breast cancer pathologic complete response to neoadjuvant chemotherapy in …

M Caballo, WBG Sanderink, L Han… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Breast cancer response to neoadjuvant chemotherapy (NAC) is typically
evaluated through the assessment of tumor size reduction after a few cycles of NAC. In case …

Assessment of response to neoadjuvant systemic treatment in triple-negative breast cancer using functional tumor volumes from longitudinal dynamic contrast …

B Panthi, BE Adrada, RP Candelaria, MS Guirguis… - Cancers, 2023 - mdpi.com
Simple Summary Neoadjuvant systemic therapy (NAST) is given before surgery to reduce
tumor burden in patients with triple-negative breast cancer (TNBC), which is an aggressive …

A radiomics model based on synthetic MRI acquisition for predicting neoadjuvant systemic treatment response in triple-negative breast cancer

KP Hwang, NA Elshafeey, A Kotrotsou… - Radiology: Imaging …, 2023 - pubs.rsna.org
Purpose To determine if a radiomics model based on quantitative maps acquired with
synthetic MRI (SyMRI) is useful for predicting neoadjuvant systemic therapy (NAST) …

Diffusion Tensor Imaging for Characterizing Changes in Triple‐Negative Breast Cancer During Neoadjuvant Systemic Therapy

BC Musall, DE Rauch, RMM Mohamed… - Journal of Magnetic …, 2024 - Wiley Online Library
Background Assessment of treatment response in triple‐negative breast cancer (TNBC) may
guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) …

Predictive value of multiparametric MRI for response to single-cycle induction chemo-immunotherapy in locally advanced head and neck squamous cell carcinoma

K Hellwig, S Ellmann, M Eckstein… - Frontiers in …, 2021 - frontiersin.org
Objectives To assess the predictive value of multiparametric MRI for treatment response
evaluation of induction chemo-immunotherapy in locally advanced head and neck …

Visual evaluation of ultrafast MRI in the assessment of residual breast cancer after neoadjuvant systemic therapy: A preliminary study association with subtype

M Honda, M Kataoka, M Iima, R Ota, A Ohashi… - Tomography, 2022 - mdpi.com
The purpose of this study was to investigate the diagnostic performance of ultrafast DCE (UF-
DCE) MRI after the completion of neoadjuvant systemic therapy (NST) in breast cancer. In …

Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer

CE Stowers, C Wu, Z Xu, S Kumar, C Yam… - Radiology: Artificial …, 2024 - pubs.rsna.org
“Just Accepted” papers have undergone full peer review and have been accepted for
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …