Radiogenomics: a key component of precision cancer medicine

Z Liu, T Duan, Y Zhang, S Weng, H Xu, Y Ren… - British Journal of …, 2023 - nature.com
Radiogenomics, focusing on the relationship between genomics and imaging phenotypes,
has been widely applied to address tumour heterogeneity and predict immune …

Integration of artificial intelligence in lung cancer: Rise of the machine

C Ladbury, A Amini, A Govindarajan… - Cell Reports …, 2023 - cell.com
The goal of oncology is to provide the longest possible survival outcomes with the
therapeutics that are currently available without sacrificing patients' quality of life. In lung …

Artificial intelligence in lung cancer imaging: unfolding the future

M Cellina, M Cè, G Irmici, V Ascenti, N Khenkina… - Diagnostics, 2022 - mdpi.com
Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays
an essential role in each phase of lung cancer management, from detection to assessment …

[HTML][HTML] Precision oncology provides opportunities for targeting KRAS-inhibitor resistance

M Sattler, A Mohanty, P Kulkarni, R Salgia - Trends in Cancer, 2023 - cell.com
Novel inhibitors targeting Kirsten rat sarcoma virus homolog (KRAS) KRAS G12C in various
cancers have shown good initial efficacy, but therapy-related drug resistance eventually …

Artificial intelligence and allied subsets in early detection and preclusion of gynecological cancers

P Garg, A Mohanty, S Ramisetty, P Kulkarni… - … et Biophysica Acta (BBA …, 2023 - Elsevier
Gynecological cancers including breast, cervical, ovarian, uterine, and vaginal, pose the
greatest threat to world health, with early identification being crucial to patient outcomes and …

Preoperative MRI‐based radiomics of brain metastasis to assess T790M resistance mutation after EGFR‐TKI treatment in NSCLC

Y Fan, L He, H Yang, Y Wang, J Su… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Preoperative assessment of the acquired resistance T790M mutation in patients
with metastatic non‐small cell lung cancer (NSCLC) based on brain metastasis (BM) is …

Radiological artificial intelligence-predicting personalized immunotherapy outcomes in lung cancer

LC Roisman, W Kian, A Anoze, V Fuchs… - NPJ Precision …, 2023 - nature.com
Personalized medicine has revolutionized approaches to treatment in the field of lung
cancer by enabling therapies to be specific to each patient. However, physicians encounter …

Predicting the initial treatment response to transarterial chemoembolization in intermediate-stage hepatocellular carcinoma by the integration of radiomics and deep …

J Peng, J Huang, G Huang, J Zhang - Frontiers in Oncology, 2021 - frontiersin.org
Objectives We aimed to develop radiology-based models for the preoperative prediction of
the initial treatment response to transarterial chemoembolization (TACE) in patients with …

Multiregional radiomics of brain metastasis can predict response to EGFR-TKI in metastatic NSCLC

Y Fan, X Wang, Y Dong, E Cui, H Wang, X Sun, J Su… - European …, 2023 - Springer
Objectives To develop radiomics signatures from multiparametric magnetic resonance
imaging (MRI) scans to detect epidermal growth factor receptor (EGFR) mutations and …

Review of current principles of the diagnosis and management of brain metastases

AW Brenner, AJ Patel - Frontiers in Oncology, 2022 - frontiersin.org
Brain metastases are the most common intracranial tumors and are increasing in incidence
as overall cancer survival improves. Diagnosis of brain metastases involves both clinical …