-
Article
Open AccessCan blood-based markers predict RECIST progression in non-small cell lung cancer treated with immunotherapy?
In this study, we aimed to evaluate the potential of routine blood markers, serum tumour markers and their combination in predicting RECIST-defined progression in patients with stage IV non-small cell lung can...
-
Article
Open AccessMulti-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study
Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study emplo...
-
Article
Open AccessA whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?
The search for understanding immunotherapy response has sparked interest in diverse areas of oncology, with artificial intelligence (AI) and radiomics emerging as promising tools, capable of gathering large am...
-
Article
Artificial intelligence in immunotherapy PET/SPECT imaging
Immunotherapy has dramatically altered the therapeutic landscape for oncology, but more research is needed to identify patients who are likely to achieve durable clinical benefit and those who may develop unac...
-
Article
Open AccessRadiomic signatures from T2W and DWI MRI are predictive of tumour hypoxia in colorectal liver metastases
Tumour hypoxia is a negative predictive and prognostic biomarker in colorectal cancer typically assessed by invasive sampling methods, which suffer from many shortcomings. This retrospective proof-of-principle...
-
Article
Open AccessIs the generalizability of a developed artificial intelligence algorithm for COVID-19 on chest CT sufficient for clinical use? Results from the International Consortium for COVID-19 Imaging AI (ICOVAI)
Only few published artificial intelligence (AI) studies for COVID-19 imaging have been externally validated. Assessing the generalizability of developed models is essential, especially when considering clinica...
-
Article
Open AccessArtificial intelligence-based diagnosis of asbestosis: analysis of a database with applicants for asbestosis state aid
In many countries, workers who developed asbestosis due to their occupation are eligible for government support. Based on the results of clinical examination, a team of pulmonologists determine the eligibility...
-
Chapter
The Future of Artificial Intelligence Applied to Immunotherapy Trials
Clinical trials serve as a barrier of entry for new interventions and treatments prior to implementation in routine clinical practice. At its essence, the primary role of a clinical trial is to monitor a patie...
-
Article
Open AccessRadiomics-based machine learning differentiates “ground-glass” opacities due to COVID-19 from acute non-COVID-19 lung disease
Ground-glass opacities (GGOs) are a non-specific high-resolution computed tomography (HRCT) finding tipically observed in early Coronavirus disesase 19 (COVID-19) pneumonia. However, GGOs are also seen in othe...
-
Article
Open AccessMRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer
Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of pat...
-
Article
Machine learning-based analysis of CT radiomics model for prediction of colorectal metachronous liver metastases
Early identification of patients at risk of develo** colorectal liver metastases can help personalizing treatment and improve oncological outcome. The aim of this study was to investigate in patients with co...
-
Article
Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging MRI in rectal cancer
To compare the performance of advanced radiomics analysis to morphological assessment by expert radiologists to predict a good or complete response to chemoradiotherapy in rectal cancer using baseline staging ...
-
Article
Tumor detectability and conspicuity comparison of standard b1000 and ultrahigh b2000 diffusion-weighted imaging in rectal cancer
To compare tumor detectability and conspicuity of standard b = 1000 s/mm2 (b1000) versus ultrahigh b = 2000 s/mm2 (b2000) diffusion-weighted imaging (DWI) in rectal cancer.
-
Article
Open AccessRadiogenomics: bridging imaging and genomics
From diagnostics to prognosis to response prediction, new applications for radiomics are rapidly being developed. One of the fastest evolving branches involves linking imaging phenotypes to the tumor genetic p...
-
Article
Prenatal planning of placenta previa: diagnostic accuracy of a novel MRI-based prediction model for placenta accreta spectrum (PAS) and clinical outcome
To investigate the diagnostic accuracy of MRI for placenta accreta spectrum (PAS) and clinical outcome prediction in women with placenta previa, using a novel MRI-based predictive model.
-
Article
Open AccessRadiomics: a critical step towards integrated healthcare
Medical imaging is a vital part of the clinical decision-making process, especially in an oncological setting. Radiology has experienced a great wave of change, and the advent of quantitative imaging has provi...
-
Article
Open AccessAuthor Correction: Deep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR
A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.
-
Article
Open AccessDiffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas
We hypothesized that machine learning analysis based on texture information from the preoperative MRI can predict IDH mutational status in newly diagnosed WHO grade II and III gliomas. This retrospective study in...
-
Article
Open AccessDeep Learning for Fully-Automated Localization and Segmentation of Rectal Cancer on Multiparametric MR
Multiparametric Magnetic Resonance Imaging (MRI) can provide detailed information of the physical characteristics of rectum tumours. Several investigations suggest that volumetric analyses on anatomical and fu...
-
Chapter and Conference Paper
Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition
In this paper, we present a multi-modal medical image classification framework classifying brain tumor glioblastomas in genetic classes based on DNA methylation status. The framework makes use of computational...
