[HTML][HTML] Classifying the evolutionary and ecological features of neoplasms
Neoplasms change over time through a process of cell-level evolution, driven by genetic
and epigenetic alterations. However, the ecology of the microenvironment of a neoplastic …
and epigenetic alterations. However, the ecology of the microenvironment of a neoplastic …
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches
Radiomics describes a broad set of computational methods that extract quantitative features
from radiographic images. The resulting features can be used to inform imaging diagnosis …
from radiographic images. The resulting features can be used to inform imaging diagnosis …
Radiomics: images are more than pictures, they are data
In the past decade, the field of medical image analysis has grown exponentially, with an
increased number of pattern recognition tools and an increase in data set sizes. These …
increased number of pattern recognition tools and an increase in data set sizes. These …
Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma …
P Prasanna, J Patel, S Partovi, A Madabhushi… - European …, 2017 - Springer
Objective Despite 90% of glioblastoma (GBM) recurrences occurring in the peritumoral brain
zone (PBZ), its contribution in patient survival is poorly understood. The current study …
zone (PBZ), its contribution in patient survival is poorly understood. The current study …
Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging
E Sala, E Mema, Y Himoto, H Veeraraghavan… - Clinical radiology, 2017 - Elsevier
Tumour heterogeneity in cancers has been observed at the histological and genetic levels,
and increased levels of intra-tumour genetic heterogeneity have been reported to be …
and increased levels of intra-tumour genetic heterogeneity have been reported to be …
Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques
Background MRI characteristics of brain gliomas have been used to predict clinical outcome
and molecular tumor characteristics. However, previously reported imaging biomarkers have …
and molecular tumor characteristics. However, previously reported imaging biomarkers have …
Optimizing cancer treatment using game theory: a review
Importance While systemic therapy for disseminated cancer is often initially successful,
malignant cells, using diverse adaptive strategies encoded in the human genome, almost …
malignant cells, using diverse adaptive strategies encoded in the human genome, almost …
Darwinian dynamics of intratumoral heterogeneity: not solely random mutations but also variable environmental selection forces
Spatial heterogeneity in tumors is generally thought to result from branching clonal evolution
driven by random mutations that accumulate during tumor development. However, this …
driven by random mutations that accumulate during tumor development. However, this …
Quantitative imaging of cancer in the postgenomic era: Radio (geno) mics, deep learning, and habitats
Although cancer often is referred to as “a disease of the genes,” it is indisputable that the
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
(epi) genetic properties of individual cancer cells are highly variable, even within the same …
Intratumoral spatial heterogeneity at perfusion MR imaging predicts recurrence-free survival in locally advanced breast cancer treated with neoadjuvant chemotherapy
Purpose To characterize intratumoral spatial heterogeneity at perfusion magnetic resonance
(MR) imaging and investigate intratumoral heterogeneity as a predictor of recurrence-free …
(MR) imaging and investigate intratumoral heterogeneity as a predictor of recurrence-free …